Building strong relationships with key partners to create a robust retail media network ensures you continue to deliver enhanced value to your customers and brand partners.

According to McKinsey, and are projected to reach $100 billion in three years – making them the next big thing in advertising.

This rapid shift is transforming how brands interact with consumers and how retailers generate new revenue streams by monetizing their shopper data. But what are these networks and what’s fueling their growth?

What is a retail media network?

A retail media network is an advertising platform managed by a retailer to manage its ad inventory and control the placement of ads from various brands across its owned channels (digital, in-store, etc.) and other paid media channels. This includes ads and videos on its website, app, and in-store digital displays and banners.

These networks are made up of three main components: the advertiser (the brand or media buyer), the publisher (the retailer owning the digital and physical points of purchase), and a technology platform that connects them.

Fueling retail media networks

There are several factors currently driving the growth of retail media networks. These are:

• The rise of ecommerce – the shift to online shopping has given retailers access to a wealth of first-party data, including consumer purchase behaviors, preferences, and demographics. This enables them to target consumers and create new revenue streams by monetizing their advertising – all while reducing spend
• Cookie deprecation and the need for first-party data – with Google’s deprecation of third-party cookies, brands are seeking data collection and targeting alternatives. Retailers, armed with extensive first-party customer data, are well-positioned to fill this gap, which encourages them to collaborate closely with retail media networks to create more personalized advertising
• The disruption of traditional channels – traditional advertising channels, such as TV, have been shrinking for several years, and recent declines in ad revenues for established platforms like Meta and Google signal significant disruption in the rapidly changing advertising ecosystem. However, retail media networks provide brands with the ability to display ads to high-intent consumers closer to the point of purchase, which helps increase conversion rates
• The presence of lucrative margins – the prospect of setting up a retail media business is highly lucrative for retailers as it can significantly impact their profitability. For example, , an increase of over 24% compared to the previous year
• The rise of non-endemic advertisers – beyond traditional retail brands like CPGs, non-endemic brands are also benefiting from retail media networks. Walmart Connect, Walmart’s ad platform, has started offering offsite media to brands that do not sell at Walmart but offer complementary products and services. This approach positively impacts businesses outside of the retail sector such as automotive, entertainment, financial services, fast-food, and travel providers.

Collaboration builds successful retail media networks

In conclusion, while the potential of retail media networks is immense, it’s still very early days. Retailers need to build an entire ecosystem of capabilities from media operating models and streamlined workflows to the right partnerships with agencies, all while providing a personalized experience for shoppers and enhanced campaign performance for advertisers’ retail media spend.

Even with a robust process and advanced technology, scaling media planning, activating many channels simultaneously, and measuring across multiple advertisers seamlessly remains challenging for many retailers. The increasing deployment of Gen AI and intelligent automation solutions can help accelerate speed to market for campaign activations and provide tangible results for brands and retailers.

Building a robust and successful retail media network is a journey. Nurturing strong relationships with key partners is an effective way of ensuring you continue to deliver enhanced value to your customers and brand partners.

To learn how ÎÚÑ»´«Ã½â€™s Connected Marketing Operations is helping Albertson’s Media Collective leverage intelligent process automation and Gen AI to create ad formats, bolster media planning capabilities, and build precise audience segmentation, contact: abha.singh@capgemini.com or isha.b.gupta@capgemini.com

This summer’s introduction of the Markets in Crypto-Assets () is a significant step toward the harmonization of cryptocurrency regulation at the EU level. The new rules will help businesses better protect their assets — as well as those of customers and investors.

In July 2023 the European Supervisory Authorities published the first of three consultation packages on the June 2023 MiCA regulation. The regulation builds on a previously fragmented approach to crypto-asset requirements, which relied on national legislation and the extension of existing EU regulations, such as , to capture cryptocurrency.

The consultation will be run by the two authorities supervising MiCA compliance at the EU-level: the European Banking Authority (EBA) and the European Securities and Markets Authority (ESMA). The authorities will seek feedback from the public on technical standards and measures – such as the monitoring, detection and notification of market abuse, record keeping, sustainability indicators and governance – before they’re implemented in 2024.

MiCA – What Is It and What’s in Scope?

Part of the wider EU Digital Finance Package, MiCA brings crypto-assets, their issuers and service providers under one regulation. The regulation seeks to improve market integrity, consumer protection and financial stability – as well as promoting innovation and the use of crypto-assets. One welcome change to consumers is that crypto-asset service providers (CASPs) will have to protect users’ wallets and investors from investment and fraud risks. Market abuse, including market manipulation and insider dealing, will also be tightly regulated.

Stablecoin issuers and businesses that offer crypto-currency exchange, custody and advisory services — such as portfolio management advice — are all captured under MiCA. The new rules classify the following three types of crypto-assets:

• E-money tokens (EMTs)
• Asset-referenced tokens (ARTs)
• Utility tokens

The EBA will be supervising issuers of “significantâ€� EMTs and ARTs, while ESMA will supervise “significantâ€� CASPs (those with at least 15 million active users) [source: ]. National-level authorities will supervise non-significant crypto-currency issuers and service providers.

MiCA also presents opportunities for businesses; those successful in obtaining authorization from one EU country will be able to conduct business, or “passport� across the entire EU. This not only promotes business growth but creates a gold standard for crypto-asset businesses in the EU and across the world.

MiCA and Anti-Money Laundering (AML)

The introduction of MiCA contributes to the fight against money laundering, as compliance with the EU 4^th Money Laundering Directive (4MLD) is one of the authorization requirements. Crypto-asset providers that are in scope of MiCA will have to demonstrate how they meet the 4MLD rules ().

For example, crypto-asset service providers will have to conduct Know Your Customer (KYC) checks on all their clients and conduct demonstrable  on customers from EU High Risk Third Countries, as these have been identified as having deficient AML/CFT regimes ().

MiCA also goes hand in hand with the EU “Travel Rule� which now extends to crypto-assets. The regulation requires payment originator and beneficiary information to be provided and stored, ensuring the traceability of crypto assets and enabling suspicious activity is detected, investigated and reported. Crypto-asset service providers will also have to demonstrate how they apply a risk-based approach to the monitoring of customers throughout their lifecycle, among other anti-money laundering measures under 4MLD.

Preparing for MiCA’s Impact on Businesses

The main impact that MiCA will have on business relates to the authorization requirements for CASPs. In order to obtain authorized status, CASPs will be required to have a physical presence and effective management within the EU; satisfy general obligations toward prudential safeguarding, governance, compliance and AML; and meet specific obligations towards commercial policies and the firm price of assets. Beyond these, there will be minimum capital requirements, and, for CASPS providing advice and portfolio management, requirements around quarterly reporting and marketing communications.

The best way to be MiCA-ready is to start preparing now.

While MiCA will enter into force in 2024, there is a lengthy implementation process that can take four to five months, and certain EU countries have already started holding consultations with companies on how to obtain authorization. It will be important for new and existing market participants alike to have a detailed understanding of the MiCA requirements, as well as existing market regulations, including the , in order to successfully obtain authorization.

As CASPs face increased regulatory scrutiny, firms would need to heighten scrutiny to prevent compliance breaches, respond to risk, remediate major issues, monitor ongoing business activities, and expand digital asset product offerings safely.

Learn how we can help CASPs align their AML compliance programs with internationally recognized financial services industry standards and European regulatory expectations.

In the wake of high-profile bank collapses and increased regulatory scrutiny, banks are more reluctant to open their doors to virtual asset service providers (“VASPs�). For risk wary banks, VASPs with strong financial crime compliance (“FCC�) programs are among the most appealing customers in the cryptocurrency industry. But it can be tricky for VASPs to determine what a sound FCC program should look like, particularly in areas such as model validation, where regulatory requirements are not always clear and the considerations for transactions posted on the blockchain do not fit neatly into existing frameworks. In this article, the experts at Exiger assess and explain regulatory requirements for a model validation from across the globe, the nuances of model validations for VASPs, and why independent model validations for all VASPs should be a key component of an FCC program.

What is a Model Validation?

Automated transaction monitoring systems alerting for potential money laundering and sanctions screening systems are only useful if they operate properly. Model validation verifies that the models used to combat financial crime operate as expected, according to the business uses and objectives for which they were designed; how they are governed; their integration with the risk assessment of the institution; operational and conceptual soundness; and data quality.

According to the , model validation includes:

• Evaluation of Conceptual Soundness. This element involves assessing the quality of the model design and construction, as well as review of documentation and empirical evidence supporting the methods used and variables selected for the model. This step in validation should ensure that judgment exercised in model design and construction is well informed, carefully considered, and consistent with published research and with sound industry practice.
• Ongoing Monitoring. This step in validation is done to confirm that the model is appropriately implemented and is being used and performing as intended. It is essential to evaluate whether changes in products, exposures, activities, clients, or market conditions necessitate adjustment, redevelopment, or replacement of the model and to verify that any extension of the model beyond its original scope is valid. Benchmarking can be used in this step to compare a given model’s inputs and outputs to estimates from alternatives.
• Outcomes Analysis. This step involves comparing model outputs to corresponding actual outcomes. Back-testing is one form of outcomes analysis that involves the comparison of actual outcomes with model forecasts during a sample time period not used in model development at a frequency that matches the model’s forecast horizon or performance window.

Although this guidance was directed at banks and issued long before VASPs were on regulators’ radars, these general elements of sound model validation are applicable to any financial industry.

Further, New York Department of Financial Services (“NY DFS�) Part 504 applies to VASPs registered in New York state, and even if it may not strictly apply to VASPs, it provides strong guidance on the areas of testing that should be performed. NY DFS Part 504 includes requirements that transaction monitoring and sanctions screening programs:

• Validate the integrity, accuracy, and quality of data;
• Be based on the institution’s risk assessment;
• Maintain detection scenarios that are designed to detect money laundering or other suspicious or illegal activities; and
• Perform end-to-end pre- and post-implementation testing of the systems.

The NY DFS Part 504 model validation framework may eventually be mirrored by other regulators and includes best practice requirements in model validations. However, as discussed in the next section, VASPs are not identical to banks or other financial institutions, and there are nuances to VASP model validation.

How are Model Validation Considerations for VASPs Different than for Banks?

VASPs have unique FCC considerations, and therefore they cannot be pigeon-holed into behaving exactly like banks when it comes to model validation. Everything moves with greater speed in the world of virtual assets. Information associated with virtual asset transactions can be both more and less transparent than traditional bank transactions. Blockchains provide a public, permanent and immutable ledger of transaction history. However, some coins and services, such as privacy coins and tumblers/mixers, mask the underlying person or entity behind the transaction. Further, some VASPs have lax know your customer (“KYC�) controls and may not know if malign users have accessed their platform, and some transactions involve transfers to wallets that are not hosted on an exchange at all, and thus do not have any KYC requirements.

Traditional transaction monitoring controls only generate alerts based on information accessible to the bank – i.e., transactions where the bank is a participant. Digital ledgers provide full visibility into all the transactions (and wallets) occurring for the entire history of the digital currency. This creates new opportunities and challenges. For example, you can see if the bitcoin or wallet in a specific transactions has ever been associated with a wallet with a nexus to a sanctioned entity, but how many steps away should a VASP be from that transaction so that the VASP feels comfortable stating is has no association with that sanctioned entity? The answer lies in VASP’s risk and reputational tolerance, and how transaction monitoring and sanctions screening systems are configured.

Digital ledgers offer a world of information that may inform customer risk rating models, such as the types of products customers are using or questionable transactions they may have been involved with, which are key to providing risk-based coverage. But VASPs may also encounter limitations as to what they can glean about customers because of privacy coins and tumblers, along with the nature of the issuer and the customer’s intended use of the virtual assets.

Many VASPs have experienced rapid growth in an uncertain regulatory environment and must adapt quickly to maintain compliance with regulators. This alone makes them different from most banks, where the pace of change is much slower. Many banks perform model validation on their FCC models annually or even less frequently, however with a rapid pace of change at VASPs, partial validation of those changes should be performed as needed to ensure that risk coverage is maintained. Once the offerings are more stable, validation frequency can be reduced.

Most virtual asset transaction monitoring controls are (i) software as a service (“SaaS�) blockchain monitoring models that take digital wallets as input and return alerts against various typologies, (ii) “traditional� SaaS models that monitor fiat onramps into the digital asset ecosystem, and (iii) custom-built typologies that monitor both blockchain and fiat data such as velocity. Even with such models acting as controls against money laundering risk, the VASP is still ultimately responsible for ensuring the models are adequate to the VASP’s risk assessment, especially if the business experiences rapid changes. Further, the VASP is ultimately responsible for ensuring the TM controls work as expected, even if the monitoring takes the form of a SaaS platform. This means that the regulator will not accept deficiencies in the vendor provided tool as an excuse for risk coverage gaps. VASPs can get a level of comfort with their vendors by requesting that the vendor provide them with assurance of the testing performed on their platform. Vendors may have independent model validations performed on their own systems, and they can provide the validation report as evidence that their tools are working as expected. However, while such a vendor provided assurance can support a VASP’s model validation, it is no substitution for additional testing tailored to the risks of the individual VASP.

Why Perform Model Validation as a VASP?

Virtual assets routinely make headlines as the payment of choice for bad actors engaged in scams, laundering proceeds of drug trafficking, and proliferation finance. The need for strong FCC among VASPs is now fully recognized. It is also recognized that VASPs are responsible for ensuring their transaction monitoring and sanctions screening systems are adequate, which can be accomplished through model validations. Failure to do so creates reputational harm and financial penalties. In 2022, for example, the New York Department of Financial Services levied a $30 million fine against a VASP because its “BSA/AML compliance program, including its transaction monitoring system, has significant deficiencies.�[2] This VASP did not have adequate staffing; did not transition from a manual transaction monitoring system that was adequate to its size, customers, and transaction volume; and did not devote sufficient resources to address risks specific to the company.

Further, VASPs that perform model validations for transaction monitoring and sanctions screening systems are more appealing to banks, who are aware that regulators will focus on high-risk customers during any regulatory exam, and banks must be prepared to answer questions about FCC risks with confidence. Thus, in addressing and reducing their FCC risks with model validations, VASPs reduce the FCC risks for the banks in which they keep their bank accounts, and improve their likelihood of partnering with a bank, or being onboarded as a bank’s customer.

Meet Regulatory Requirements

United States

The U.S. government has been a leader in applying its anti-money laundering and countering the financing of terror (“AML/CFT�) framework to virtual assets. U.S. regulators, including FinCEN, SEC, CFTC, and OFAC, have issued interpretive and clarifying guidance since 2013 to . The last several years have seen U.S. regulators “examining financial institutions providing virtual assets-related services for compliance with registration, AML/CFT, and sanctions obligations and have taken enforcement actions against non-compliant institutions.� Such institutions have recently seen monetary penalties, enforcement actions, and settlement agreements. Because of this increased scrutiny, the U.S. Department of the Treasury has created several priority actions related to digital assets, including improving global AML/CFT regulation and enforcement, updating BSA regulations, strengthening U.S. AML/CFT supervision of virtual asset activities, holding illicit actors accountable, and engaging with the private sector.

In accordance with , VASPs are subject to the Bank Secrecy Act.

VASPs doing business wholly or in substantial part in the United States qualify as money transmitters, which means they are required to comply with the BSA obligations that apply to MSBs, including registering with FinCEN; developing, implementing, and maintaining an effective AML program; filing SARs and currency transaction reports (CTRs); appointing a chief compliance officer; conducting training; and maintaining certain records. When operators of these VASPs violate the BSA or neglect regulatory requirements, such as failing to establish effective AML programs or report suspicious activities, their actions present a vulnerability to the financial system.
U.S. Department of the Treasury (2023), Digital Assets Action Plan

Increased penalties and scrutiny further highlight the need for VASPs to have transaction monitoring and sanctions screening systems in place. These will help mitigate the risk of money laundering and sanctions, and a model validation is a key part of this process. An independent model validation will bring industry experts who can benchmark model effectiveness.

At the state level, VASPs subject to NY DFS regulations must adhere to on . These requirements include matching BSA/AML risks to the institution’s products, services, and customers; end-to-end pre- and post-implementation testing of the systems; validation of data and data sources; and governance and management oversight. Therefore, all NY DFS regulated VASPs should include model validation as part of their compliance program.

VASPs in the United States are subject to U.S. Department of the Treasury’s Financial Crimes Enforcement Network (FinCEN) and Office of Foreign Assets Control (OFAC) regulations. Cryptocurrency exchanges have faced fines, settlements, and consent orders related to violations of the Bank Secrecy Act (BSA) and other FinCEN

In July 2020, the Office of the Comptroller of the Currency (OCC) issued an concluding that national banks may provide cryptocurrency custody services on behalf of customers provided it can demonstrate that it has controls in place to . Specifically, the OCC supervisory office will review the bank’s risk management systems and controls and risk measurement systems. This includes having systems in place to identify, measure, monitor, and control operational and compliance risk (specifically, BSA, anti-money laundering, and sanctions requirements).

FATF

The Financial Action Task Force (“FATF�) recommends that VASPs be regulated for AML/CFT purposes, licensed or registered, and subject to effective systems for Therefore, VASPs’ obligations match those of traditional financial institutions and include transaction monitoring and sanctions compliance.

There has been recent progress in introducing FATF’s Travel Rule, which requires the private sector to obtain/exchange beneficiary and originator information with . The Travel Rule is a key requirement that enables the private sector to comply with transaction monitoring and sanctions screening requirements. FATF considers it a key priority for the private sector to strengthen efforts to facilitate interoperability across Travel Rule technological solutions

United Kingdom

Cryptoasset businesses in the United Kingdom must be registered with the FCA. The FCA’s Money Laundering Regulations (“MLRs�) include the requirement of businesses to show that it has policies, controls, and procedures in place to effectively manage money laundering and terrorist financing risks proportionate to the size and nature of the business’s services. This includes customer due diligence, ongoing monitoring of customers and transactions, and establishing an independent internal audit function.

Singapore

The Monetary Authority of Singapore (MAS) implemented the in 2020 whereby MAS issues licenses to digital payment token services. The majority of applicants have been rejected due to stringent MAS standards. The MAS requires payment service providers to have appropriate transaction monitoring systems in place, with the degree of automation and sophistication dependent on the size and complexity of the payment service provider’s operations. This system should be independently validated and the parameters and thresholds should be .

Hong Kong

The Hong Kong Monetary Authority (HKMA) is currently developing a that licenses VASPs and subjects them to comprehensive regulatory framework covering anti-money laundering and counter-terrorist financing, governance, audits, risk management, and more. This regime is targeted for implementation by 2024.

Australia

Digital currency exchanges with a geographical link to Australia must register with the Australian Transactions Reports and Analysis Centre (AUSTRAC) and meet AML/CTF . The Australian government is developing new regulations specific to digital currency exchanges, which it proposes to call Crypto Asset Secondary Service Providers (CASSPRs). Current regulations do not specify whether digital assets are financial products and subject to the Australian Securities and Investments Commission or a consumer product regulated under the Australian Competition and Consumer Commission. The proposed obligations for CASSPRs include regular independent audits and compliance with AML/CTF provisions.

Disclaimer: This blog article explores potential futures in software engineering based on current advancements in generative AI. While the content presents a plausible vision, it cannot predict the future. Our purpose is to inspire software engineers, software companies and enterprises who are embracing the next generation of ‘product-centric’ business models driven by software to anticipate and embrace the transformative potential of generative AI with bold and forward-looking actions and strategies.

The AI evolution: Transforming software engineering

In the past year, the landscape of tech has seen unprecedented upheaval. Generative AI (GenAI) has catapulted data science, machine learning, and AI into the limelight, sparking conversations and at all levels of business and democratizing access to the power of AI.  From the boardroom to dining room tables around the world, there’s no question that the GenAI evolution will profoundly reshape humanity’s relationship with technology.

Among the many impacts of GenAI, one of the greatest transformations underway is that of Software & Platform Engineering.  As a core capability for every product-centric enterprise in a world that runs on software, this critical domain is being reshaped before our eyes and the impact will be profound.  Every industry is experiencing disruption and reinvention. From software itself to AI-powered products and services, this paradigm shift will be felt.

GenAI is taking these advancements to the next level with a new era of “Generative Software & Platform Engineering.” This concept elevates software to new heights, with visions of enabling it to adapt, scale, and evolve autonomously in response to a dynamic environment.

Just as object-oriented languages and cloud concepts revolutionized software development, GenAI promises to unlock unprecedented possibilities for resilient systems that drive progress in the digital age. To survive, compete and thrive in this context, enterprises must not only adopt Generative AI – but must quickly evolve and mature their core Software & Platform Engineering capabilities.

Unlocking the potential of generative software engineering: Lessons from the past, projections for the future

The transformative journey of software engineering, from procedural development to object-oriented programming, to cloud and microservices, revolutionized how we build and maintain software. Generative Software Engineering is poised to drive an even greater leap forward. Fueling this evolution is Generative AI, a game-changer that empowers software entities to autonomously generate, test, deploy and maintain code.

Inspired by the adaptability of living organisms, these entities will transcend the constraints of a traditional development lifecycle. Guided by human-defined principles, they will orchestrate their capabilities to evolve and optimize in real-time.

The evolution of microservices architecture lays the foundation for Generative Software Engineering. By leveraging Generative AI, we can create Generative Microservices. Eventually, these autonomous entities will seamlessly rewrite themselves to meet fluctuating demands, enhance performance, and integrate with other services. This will lead to the emergence of perpetually optimized software systems that require minimal human intervention.

Generative AI will act as a catalyst, propelling MACH (Microservices, API-first, Cloud-native, Headless) principles to new heights. It will enable the development of self-evolving, API-first software that can autonomously generate new APIs based on user behavior. Cloud-native systems will be empowered to seamlessly migrate across providers to optimize for both cost and performance.

Generative AI will pave the way for “sense and respond” enterprises, where software platforms are inherently dynamic and responsive. This will empower businesses to create new business models that continuously adapt and thrive in the ever-evolving digital landscape.

The human element – adopting and evolving alongside AI

To meet the potential of this vision, realize its value and create a positive future for humans involved in software engineering will require a planned, considered transformation for the human beings involved in software engineering.  To effectively manage this road ahead, organizations need to have a vision and roadmap for adoption, acceleration and elevation of human skills, roles and value.

Generative AI in its present form has the power to take on the role of ‘co-developer’ as the proliferation of coding assistants, generative SDLC tools and Gen AI powered utilities rapidly become integrated into IDEs and traditional software engineering toolchains.  These will quickly lead to increasingly autonomous agents that will essentially become ‘digital developers’ on human-AI development teams.  This first phase – already well underway – is focused on adoption for productivity, efficiency, and quality gains throughout the software development lifecycle.  As the technology evolves, tools mature, and adoption reaches a state of near ubiquity, we expect many organizations will struggle to cross the chasm between experimentation and maturity at scale. 

On the other side of that chasm lies the realization of the vision and value of the Generative Software Engineering Era.  In this future, those organizations who have successfully made the transformative leap will see humans working in more creative, high-value roles that increasingly focus on the orchestration of Generative AI agents who do the heavy lifting of software engineering under the conceptual and value-oriented direction of human experience engineers.

Traditional roles in the software engineering lifecycle will become more strategic and focused on faster iteration of product engineering lifecycles, accelerated value growth and oversight of product and platform quality.  Increasingly, platform engineering teams will focus on the supervision of adaptive product roadmaps that quickly respond to new user preferences, market opportunities and emergent business models. While much of the short-term focus is currently on the productivity and efficiency aspect of Generative AI’s potential – the far more powerful and exciting future lies in the new value it can unlock and the promise it holds to vastly expand the scope and impact that human beings have through building software in this new paradigm.

Dynamic software co-creation

Generative Software Engineering heralds a future wherein human ingenuity, human innovation and human goals and opportunities are the driving force behind dynamic creation of software products, platforms and services.  Future software products will take direction and orchestration from sophisticated software product orchestrators, highly-skilled in collaborative software creation in concert with autonomous software engineering agents. Guided by high-level objectives and constraints, these agents will autonomously generate code, perform testing, and deploy updates, much like a highly skilled developer.

Not only will they respond to direct human instructions but in this new era, software products and platforms will evolve in real-time, driven by sophisticated analysis of user data, preferences,  interactions and market insights. Generative AI will enable software to self-optimize, self-configure, and even self-expand its features and capabilities in response to this analysis. This will lead to the co-creation of highly personalized user experiences, with software automatically adjusting such aspects as its interface, performance, and functionality to suit individual and organizational user needs and preferences.

Foundations for success

These prospects for the Brave New World of Generative Software Engineering are both incredibly inspiring and significantly daunting.  The rapid pace of change is driving an ever-widening gap between the future value and current realities for the great majority of enterprises.  At ÎÚÑ»´«Ã½, our experience suggests that every organization in the business of building software or adopting a platform & product-centric mindset as a strategic growth imperative must act now with commitment and bold vision to prepare for success in the age of Generative Software Engineering.  While the foundational building blocks are also evolving, our work with clients and in our own internal GenAI transformation has given us insight to some key domains of focus to jumpstart the transformation while bringing immediate value.  We highlight in the next section a set of critical success factors we believe will underpin a bright horizon of possibilities for Generative Software & Platform driven enterprises.

Have a roadmap – Seldom do we wind up anywhere meaningful without plotting a course.  Plotting a wayfinding course implies a destination both sufficiently valuable and sufficiently defined to get there.  Perhaps nowhere is this concept more crucial than in the realm of Generative Software Engineering.  Our Point of View is that those enterprises who define an inspiring and powerful “North Starâ€� for their unique Generative Software future and a considered roadmap to guide them ever in that direction will attain much greater success than those (the majority at present) who fail to drive their iterative experiments, ideation and use cases without a vision and dynamic roadmap to value.

Employ Framework thinking – from innovation frameworks adapted to the world of Generative AI to Software Engineering methodology frameworks that guide increasing maturity, skillsets and roles, to technical frameworks for the industrialization of GenAI software product engineering at scale.  In the Generative AI world, things will become far more complex and possibly chaotic.  In light of such realities, a grounding in frameworks will be essential to scaling and accelerating value realization in building software.  This is why we highlight the importance of maturity in development and engineering practices.  Many enterprises remain in fractured states of evolution when it comes to software engineering.  Success in the Generative Era requires a product-centric, platform engineering rigor that will bring every organization value in itself and will position any enterprise for greater success with Generative Software Engineering.

Transform end-to-end – a future-ready, Generative Software Engineering enterprise needs to think and act end-to-end, not in silos and pockets of process transformation and tool adoption.  At ÎÚÑ»´«Ã½, our own journey has a focus on prioritizing and realizing cohesive end-to-end Software Product Engineering capabilities over lots of shorter term PoC’s and use case experiments.  In short – we’re focusing on “quality over quantityâ€� with ideation, innovation and uptake experiments, so we continue to lead the market in “quantity with qualityâ€� in software innovations for our clients who are serious about leading their industries with the aid of Generative Software Engineering.

Hit the Human Element “Head Onâ€� – Traditional software engineering roles will be radically transformed in the coming years.  This will come with great challenges from organizational change dynamics to individual human anxieties to significant HR complexities. Alongside the challenges, it’s crucial to stay informed about the evolving regulatory landscape surrounding Generative AI and ensure compliance with relevant legal frameworks.

The successful leaders of the Generative Era will forge clear paths to support their valuable human resources in evolving alongside AI, engaging them in creating the future, elevating their value through enablement, empowerment and training in everything from innovation skills to data engineering, from prompt engineering to creative experience engineering and orchestration of Generative Autonomous Agents.  Rather than asking ‘what are the productivity gains’ and seeking to translate those metrics into incremental efficiencies or profits, visionary enterprises should ask ‘what is our North Star vision and roadmap for human value development in the Generative Engineering Era’.  Then, make bold investments in people as opposed to reducing their numbers.

Collaborate wisely – With a clear “North Starâ€� vision and an enterprise-specific roadmap in mind, organizations should seek to build strong partnerships with technology and services providers who can bring thought leadership, proven assets and accelerators, skills leadership and flexible options for shared value.   The need for collaboration will only intensify as the landscape of Generative AI technologies continues to grow and evolve.  Partnerships will need to move past ‘where have you done it before and what’s your price’ and into a space of ‘who are the best partners to help me adapt and evolve through the volatility of this paradigm shift’ based on capabilities, depth of understanding and creativity in collaborative value creation.

Conclusion: A future of co-creation and autonomy

Generative Software Engineering is here, and every day we’re building an exciting – if daunting – future of unprecedented acceleration in the development of robust, scalable, and user-centric software products and platforms. Just as object-oriented languages and cloud architectures opened new horizons for software development, Generative AI will pave the way for a future where software not only serves but anticipates and evolves with human needs. In this future, the role of the software engineer evolves from creator to orchestrator, guiding intelligent systems that can generate, adapt, and innovate, marking a new chapter in the symbiotic relationship between humans and their technological creations.  At ÎÚÑ»´«Ã½, in collaborative partnership with visionary industry partners like Google and its enterprise GenAI stack powered by groundbreaking models like Gemini and dynamic Google Cloud services, we’re committed to unleashing human potential through technology for an inclusive and sustainable future.  We look forward to working with you to help you build yours.

ÎÚÑ»´«Ã½ at Google Cloud Next 2024

Google Cloud Next brings together a diverse mix of developers, decision makers, and cloud enthusiasts with a shared vision for a better business future through technology. As a Luminary Sponsor, ÎÚÑ»´«Ã½ is committed to elevating the event experience with opportunities to boost learning and engagement and get fresh insight into today’s riveting topics – including generative AI.

Whether the aim is empowering businesses or their people to unlock the power of generative AI, ÎÚÑ»´«Ã½ is at the forefront of this evolution. Our continuous work in this growing domain means we are equipped to help our partners capitalize on this unique technology and engineer use cases for enhanced and unprecedented customer experiences.

Come by our booth #840 and let’s explore the possibilities of generative AI with live demos showcasing its potential for Cloud, Data/AI, and Software Engineering. Or reach out to us – we would love to hear your perspective on how we can get ready for what comes next.

The launch of ChatGPT in late 2022 propelled Generative AI to prominence, gaining significant visibility and popularity among both consumers and organizations. Telecom operators have been quick to experiment with this technology, exploring applications that would boost individual productivity and optimize industry-specific processes, like client interactions

Most recently we have seen a significant interest in applying Generative AI to Network Operations, which is an area in which CSPs (Communications Service Providers) have long sought efficiency gains to enable the management of an increasingly complex technology landscape. In this article, we explore how operators can leverage Gen AI to augment the employee experience and automate business processes, all in the name of smarter, faster, more resilient networks.

Network knowledge at your fingertips

Generative AI is a gamechanger when it comes to intelligent document querying and information retrieval. The retrieval augmented generation (RAG) pattern allows the interrogation of text indexes via a semantic representation of a query and has quickly become a standard. Based on retrieved sections of selected documents, Generative AI can easily produce summaries compliant with pre-defined templates.

This application is demonstrated with one of our clients, who is now providing network technicians with a tool that enables them to quickly access a summary of past incidents that have affected a specific node on the broadband access network. Thanks to Generative AI, the new tool can retrieve all incidents relevant to the current investigation and produce a formatted summary of past events – reducing the time for this task.

CSPs are also investigating the use of Generative AI for managing contracts, such as interconnect and roaming contracts, or cell tower lease agreements. Through the help of Gen AI-enabled tools, users can quickly search for specific clauses or ask direct questions, such as “What are the security procedures for accessing this site?” or “What is the average price for site rentals in Madrid?â€� This removes the need for extensive, complex searches for the most up-to-date and relevant contracts and amendments. It also reduces the risk of error, especially when navigating large, complex document repositories that can span several years and many geographies.

The rise of conversational interfaces

For the past 60 years, most traditional applications have been using either command-line or graphical, menu-based interfaces. While regular users have mastered these tools, occasional users struggle. This is why some customers still prefer calling the contact center instead of using a mobile app!

Generative AI gives a new dimension to user interfaces, moving from predefined, rigid dialogs, to more free-flowing and intuitive conversations. This is relevant for some of the interfaces used when operating networks, where the user experience can be much improved.

For instance, we are currently defining a proof-of-concept with one of our CSP clients to support field technicians who perform interventions at customer homes and/or network points of interest. These technicians frequently need specialized help from team leads or colleagues while in the field; if this help cannot be provided on demand, then the service agent may need to schedule a follow up intervention.

Generative AI allows the development of a conversational bot that enables the technician to get the information they need about the specific location/services and technologies that will enable them to successfully troubleshoot or deploy services. A voice bot or a chat bot makes the job of the technician easier and quicker, allowing for faster issue resolution and avoiding repeat and costly truck rolls.

These service tools can also be combined with augmented reality (AR) applications, such as using a mobile phone to scan physical devices and generate relevant information. A variety of new interfaces that enable this type of support is made possible by the emergence of multimodal models such as Google’s Gemini, OpenAI’s GPT-4 and Mistral AI’s Mistral 7B.

An additional application focuses on network configuration. Specific intents, like boosting radio capacity at a stadium ahead of a major event, are set up through dedicated interfaces that require expertise on network management applications. By employing a conversational interface, network engineers can effortlessly grasp available capacity and make configurations for upcoming activities through friendly conversations with an agent. This conversational agent doubles as an advisor, drawing insights from historical activities and the present network status.

Autonomous Networks monitoring with a human touch

Moving to a higher level of network automation is critical for network operators. In fact, this is the key to improving service quality within a more complex technological environment without adding additional staff. AI is key to moving from human-managed networks, supported by insights from data, to AI-managed networks. Generative AI can thus complement other AI models, such as anomaly detection and classification.

While the industry has settled on the term “Autonomous Networks,” the goal is not complete autonomy. Configuration of intent is essential, and ongoing network monitoring for compliance is crucial. Even with a significant level of automation, human oversight remains imperative to ensure safety and maintain the quality of service.

Generative AI can produce a human readable summary of the status and activity in the network, allowing human agents to understand if and how the intent is satisfied. Even when operating networks with a high level of automation, human agents must be able to investigate, ask specific questions and get replies.

In the same way, an Autonomous Network’s reaction to an alarm or an anomaly must be defined in advance by a network engineer. On older generations of solutions, scripts must be developed and tested, which requires strong expertise. With Generative AI, natural language could be used to define responses to alarms, going as far as to extract appropriate remediation procedures from process documents. This approach allows human experts to review and make necessary adjustments.

Leading the way in an AI revolution

Like traditional AI, there are many use cases for Generative AI in the Telecom industry. In addition to individual agent productivity tools, Generative AI can be used to refine and streamline operational processes to better manage networks.

At ÎÚÑ»´«Ã½, we are now experimenting with leading CSPs on how to augment or automate existing workflows through AI technologies, helping them create a smarter, faster, more resilient network.

TelcoÎÚÑ»´«Ã½ is a series of posts about the latest trends and opportunities in the telecommunications industry – powered by a community of global industry experts and thought leaders.

Danger, risk, breach, leak, scam, fake, fraud, theft — all words which plague consumers’ experience of financial services. As the cost-of-living crisis envelops the U.K. and the amount of vulnerable people increases, the volume of various frauds, scams and other consumer-focused financial crimes are on the rise. Firms might perceive that consumers lack understanding and are naïve, making themselves an easy target for fraud — or that consumer protection is beyond the scope of their Financial Crime Programs. However, combatting fraud or any other form of acquisitive crime that is detrimental to consumers is a regulatory responsibility. Firms that increase their capacity to protect their customers in compliance with the requirements of the  may also increase their bottom line.

Consumer trust across financial services has diminished over time with the onset of various banking crises.  of consumers fall victim to financial crime every year. Polling suggests only  of U.K. citizens trust longer-term financial products, and the number of Suspicious Activity Reports (SARs) reported in the U.K.  20% from 742,317 to 901,255 between 2021 and 2022 — the NCA  a large number of SARs as relevant to organized fraud in 2020, and in 2022 identified increased cases of fraud against members of the public as a “newâ€� “â€�. In the wake of expanding consumer vulnerability, updated guidelines and regulations have begun to appear.

Regulatory Response

Britain’s Financial Conduct Authority (FCA) published a new Consumer Duty which will apply to all new products and services from 31 July 2023. The guidelines aim to reduce and prevent the harm caused by firms via more comprehensive regulations and standard setting. Three core elements enshrine these aims:

• A 12th Consumer Principle.
• The Cross-Cutting Rules.
• The Four Outcomes.

The new  states that “a firm must act to deliver good outcomes for retail customersâ€�.

Three “Cross-Cutting Rules� underly Principle 12 and clarify the FCA’s expectations of the behaviours and standards of conduct required under the new Principle, stating firms must:

• Act in good faith towards retail customers.
• Avoid foreseeable harm to retail customers.
• Enable and support retail customers to pursue their financial objectives.

The rule to “avoid foreseeable harm to retail customersâ€� speaks to the role that Money Laundering Reporting Officers (MLROs) can play in Consumer Duty compliance. They can do this by ensuring adequate systems and controls are in place to “protect consumers from harmâ€� by preventing and detecting financial crime committed on the firm’s platform, or via the firm’s products and services. 

The Cross Cutting Rules help firms interpret the FCA’s “Four Outcomes� that dictate the conduct of firms across four key areas which define their relationship with the consumer:

• Governance of products and services.
• Price and value.
• Consumer understanding.
• Consumer support.

The Cross Cutting Rules and Four Outcomes work in tandem to set clear expectations of a firm’s culture and behaviour.  The rules apply to both retail and wholesale firms who market or sell products to retail consumers, either directly or indirectly. 

Bad for Business

The impending Consumer Duty has consolidated the FCA’s commitment to raise the bar on standards of consumer protection across financial services and to put the needs of the consumer first. The new Duty places particular emphasis on vulnerable customers, or those who may be at a greater risk of harm from the action or inaction of a firm. The new FCA guidelines confirm that firms can no longer pay lip service to consumer protection and must demonstrate they proactively identify potential points of harm in the consumer’s journey.  A proactive approach is encouraged both to ensure compliance when the Duty takes effect and to increase consumer trust in firms’ financial services — which will in turn mean an increase in financial services business.

In the face of a cost-of-living crisis, to comply with the new Consumer Duty, firms are expected to review and calibrate financial crime controls to ensure they can address emerging financial crime threats facing not just the firm but also its retail customers. For example, is the firm doing enough to raise awareness of emerging crimes such as Authorized Push Payment (APP) fraud, Account Take Overs (ATO), investment frauds, pension scams or unauthorized use of credit cards?  An affirmative answer to these questions from firms means consumers should be more secure and will feel more confident in the U.K.’s financial services sector.

Falling victim to fraud lowers consumer trust in legitimate financial products and services. Without trust in traditional financial institutions, vulnerable consumers become more susceptible to criminals whispering honeyed words of “simpleâ€�, “no paperworkâ€� or “no account neededâ€� financial services primed to defraud the consumer of their pension pot or charge ludicrous transaction fees.  Low consumer trust can be created when firms are negligent in their approach to consumer protection and think it is solely the consumer’s responsibility, or when consumer protection is outside the remit of financial crime specialists. This attitude does not align with the FCA’s guidance and could foster an environment which breeds financial crime and proves harmful to the consumer — a firm’s failure to consider the Consumer Duty from a financial crime perspective could enable the economic abuse of vulnerable customers by criminals.

To adhere to the FCA’s Principles, firms must engage with financial crime prevention anywhere where the firm has a nexus with consumers. Therefore, regardless of the relationship consumer protection has with the bottom line of a business, it is squarely the responsibility of the firm to protect consumers from harm through financial crime.

How Should MLROs React?

As the appointed person and holder of the FCA’s Senior Management Function (SMF17), it is the duty of the MLRO to react to the FCA’s guidance and translate the Consumer Duty guidance into useful actions their firm can take to minimize consumer harm through fraud and other financial crimes. MLROs should assess Consumer Duty and determine what changes they need to make to their existing Financial Crime Framework.

MLROs can improve the existing Financial Crime Framework by incorporating three amendments:

• Customer-oriented internal gap analysis and feedback loops.
• Improved customer awareness.
• Expanded internal training and culture.

Operationally, MLROs can integrate the new Consumer Duty into their existing financial crime framework by identifying where consumers fall victim to financial crime, investigating these cases thoroughly and taking appropriate action to incorporate the learnings into new or updated controls and procedures.  MLROs should also monitor news reports and publications from the National Crime Agency, CIFAS and others to identify emerging fraud and financial crime typologies that target consumers and take steps to strengthen their firm’s prevention and detection capabilities, where possible.

The FCA’s expectations of firms under the Consumer Duty echoes the core messaging of existing guidance. The official handbook lays out broad instructions such as asking firms to “put consumers at the heart of their business and focus on delivering good outcomes for customers�. This expectation guides the operational response of the MLRO as follows:

• Implement controls to prevent consumers from being victims of financial crime.
• Find where customers are victims of financial crime, identify a gap in controls and procedures, investigate and take appropriate remedial action, and then feed this back into the Financial Crime Framework for continuous improvement.  
• Consider internal and external SARs since they may provide additional information on internal control weaknesses or failures with products and services. SARs provide the MLRO an abundance of valuable data and intelligence to feed back into their Financial Crime Framework to improve consumer protection.

A conscious inclusion of consumer protection assessments into existing gap analysis, assurance activity and operational feedback loops can help to quickly upgrade a Financial Crime Framework to comply with Consumer Duty. For full effect, such operational actions can be implemented in conjunction with updated training and customer awareness campaigns.

Increased customer awareness of fraud and other forms of acquisitive crime helps improve consumer protection and can build trust between consumers and financial institutions. Lessons can be learned from campaigns initiated by the larger retail banks where interactive customer awareness resources are easily accessible. MLROs should partner with their regulatory compliance colleagues to flag consumer protection as a firm-wide mission; MLROs can help the business understand the full extent of financial crimes which can endanger consumers and help them to understand the FCA’s requirements for Consumer Duty through a financial crime lens. MLROs have the added responsibility of ensuring that their Board of Directors are appropriately informed of the additional responsibility, which can take the form of inclusion in the MLRO report submitted to the Board.

Training is a foundational pillar of any financial crime framework. Aspects of consumer protection and the new Consumer Duty can be integrated into firms’ pre-existing AML/CTF training programs — the MLRO can translate the FCA Consumer Duty requirements and guidelines into practical and consumable training resources. Folding aspects of consumer protection into existing training equips employees to fight financial crime and protect consumers from harm; educates customers interacting with customer-facing staff; and breeds a working culture which values consumer confidence and is vigilant in preventing the economic abuse of consumers.

The new Consumer Duty is not a set of recommendations which financial crime experts can ignore, but instead requires careful thought and resolute action from MLROs and their functions. Training, awareness and operations can all be updated to meet the FCA’s  â€œto deliver good outcomes for retail customersâ€�. The guidelines emphasize that the consumer nexus is an avenue for financial crime. Translation of the Consumer Duty through operational actions, training, awareness and culture ensures MLROs can effectively and proactively integrate the new Consumer Duty into their financial crime programs.

Visit our anti-financial crime – risk management and compliance page and learn how we can help your firm navigate the impending Consumer Duty by providing an end-to-end health check of a firm’s financial crime systems and controls.

Generative AI within the workplace isn’t just innovation, it is a whole new way of working. Whilst the technology has been around for some time, it hasn’t been so readily available to everyone across the workplace, and it has caused a paradigm shift transforming the very foundation of how we work, collaborate, and perform our daily tasks, promising a future rich in creativity, innovation, and peak performance.

Generative AI is fundamentally changing the way we work. It is poised to create a future of work where human and artificial intelligence work as one to achieve extraordinary outcomes.​

The onus is now on businesses to harness the opportunities the technology presents whilst also understanding its implications on security, data, and people, and to truly rethink new ways of working to fully maximize the benefits.

In less than a year since ChatGPT’s release, generative AI is now discussed in almost every boardroom – the ÎÚÑ»´«Ã½ Research Institute recently found that 96% of organizations say generative AI is on their agenda – and most are optimistic about its benefits. The next step is to turn optimism into action, and the workplace is at the epicenter of this change.

Hyper-personalization: A game-changer

In the era of generative AI, the workplace will no longer be a one-size-fits-all environment. It’s a dynamic space where services and experiences are tailored to individual preferences, work patterns, and communication styles.

With the ability to analyze colossal amounts of data, Generative AI can create a unique work environment for everyone, allowing new ways of working and opportunities for businesses to rethink the modern workplace. This hyper-personalization redefines digital engagement, collaboration, and personal performance, and transforms how we learn, develop, and perform.

Imagine AI-powered virtual assistants that understand your unique work style and dynamically optimize workflows accordingly.

Or what if you could experience personalized learning paths designed around your unique strengths and weaknesses, providing you with the precise skills you need to excel in ways that work for you so that knowledge and retention are at their maximum.

This augmented human experience shifts the focus towards innovation and creativity, makes work more enriching.

The performance renaissance

Generative AI is not just enhancing personalization; it’s redefining productivity and more excitingly it will have a transformational impact on personal performance. By integrating AI co-pilots into everyday applications, mundane tasks are automated, time is optimized, and errors are minimized. This allows employees to focus on the strategic and creative aspects of their jobs, thereby boosting their performance to new heights.

With performance enhancement copilots such as Microsoft 365 Copilot, employees now have the ability to take their performance to the next level, to be more expressive and impactful in their presentations, more creative and efficient when producing documentation, more analytical across large complex datasets, and more resourceful when engaging with communications channels such as email and instant messaging.

The transformation is all-encompassing, extending to frontline workers as well. AI copilots can optimize the performance of various professionals, from doctors to retail workers. For instance, retail assistants could leverage AI copilots that analyze customer behavior, preferences, and past purchases to provide personalized shopping experiences.

These AI-powered applications can streamline tasks, provide real-time insights, and enable frontline workers to deliver unparalleled service, thereby transforming their roles and enhancing their productivity.

Operational excellence: The new norm

Beyond enhancing workplace personalization and productivity, generative AI is fast becoming the bedrock of operational efficiency, ensuring organizations remain relevant and sustainable.

For example, AI chatbots empower customer service agents to deliver rapid and superior solutions. Agents can be trained to provide better responses, reduce issue resolution times, and gain easy access to information during customer interactions.

The impact extends to the onboarding of new colleagues who can quickly become as effective as senior agents. This not only improves service quality, but also customer perception. Agents have the ability to not only respond, but also to train AI models, further improving data quality and value.

Generative AI’s impact extends to every layer of support, from foundational operations to knowledge management, streamlining processes and reducing the burden on employees.

Our point of view – The Generative AI imperative

The advent of generative AI has ushered in a new era, ready to transform industries across the spectrum. With pace come challenges, and organizations must tread carefully, considering the ethical and social implications of AI. Privacy, security, bias mitigation, accountability, and digital inclusion should all be integral to integrating AI in all its forms across your business.

To harness the transformative potential of generative AI and reinvent the employee experience, a human-centered approach is paramount. Organizations must prioritize the needs and aspirations of their employees, engage in collaborative AI co-creation, and respect individual values and preferences.

Generative AI is not a distant wave but a powerful tide reshaping the employee experience. The extent to which an organization participates will define its future in the ever-evolving market. It’s not a race to be the fastest; it’s a commitment to being in the game, adapting to change or risking obsolescence.

In conclusion, the dawn of generative AI is an inspiring, exciting, and transformative event. It’s about unleashing a whole new way of working, enabling people to be more creative, innovative, and efficient in their roles. It’s about empowering individuals, enhancing experiences, and driving businesses forward into an exciting future.

The caveat is that the effectiveness of gen AI in the workplace hinges on your ability to manage and secure your data, move quickly to the cloud, and have an unwavering focus on your most important asset – your people.

Step into the future of work with Microsoft 365 Copilot guided by our agile, end-to-end approach that puts people at the heart of workplace transformation.

As organizations begin seriously considering their post-pandemic futures, they now face the challenge of walking the tight rope between meeting growth objectives and building sustainable businesses. 

Over the last year, promises of long-term sustainability agendas have more than tripled, with pledges of zero carbon and carbon neutrality abounding. While many organizations are turning to technology to meet these targets and solve environmental issues, enterprises need to ensure their IT does not become a part of the problem.  

The era of sustainable tech is on the rise. Companies are now leveraging innovative, data-driven technology to simultaneously streamline operations, cut carbon emissions, and reduce their carbon footprint. Often perceived as a savior rather than a sinner, the production, use, and disposal of technology has an often-overlooked carbon footprint: an estimated were generated worldwide in 2021 alone. The total is growing by an average of 2 Mt a year. 

Accelerated by the fiercely dynamic and competitive markets, more organizations are embracing digital transformation across their business. As a result, demand for computing power and data storage is on the rise and so too is the energy required to produce and run them. Curating sustainable enterprise-wide digital systems will be crucial for any business trying to balance the objectives of sustainable growth post-pandemic.   

But with so little awareness on the matter, the road to successful and sustainable IT needs a clear and rigorous roadmap. Our research has found crucial factors to consider when building and implementing sustainable IT strategies â€“ let’s have a look through each one.  

•  Understanding the task  

When it comes to strategy, half of firms have defined an enterprise-wide sustainability approach, yet less than one in five (18%) have a comprehensive, sustainable IT strategy with well-defined goals and target timelines.  

Before a clear and robust framework can be rolled out, organizations need to get clued in on what they are dealing with. Our research revealed an alarming gap in awareness regarding the overall environmental impact of IT, with fewer than half of executives (43%) globally aware of their organization’s IT footprint. Many are confused about the true impact of IT. Only 34%, for example, know that the production of mobiles and laptops has a higher carbon footprint than the usage of these devices over their lifetime.  

Getting a clear understanding of the issue is the first critical stage for firms looking to develop sustainable strategies. Once the baselines and benchmarks of an enterprise’s environmental footprint have been marked out, organizations can then look to establish, implement, and monitor key performance indicators, targets, and frameworks. 

•  Engaged and informed employees  

Employees and leaders who are engaged with sustainability agendas drive greater progress. Even the most thorough strategies can come undone when those involved are not committed to the cause. Taking things one step further by developing a specialist sustainable IT team can provide streamlined purpose and coherence. Organizations must adopt the same mindset with employees as with consumers. People want to buy from companies with sustainable products and services. Likewise, employees want to work for such organizations. People are a critical component of sustainability transformation. Therefore, you must foster a culture that celebrates and promotes environmentalism, while trusting and empowering your people to contribute their own ideas. Those who have made sustainability a pillar of the organizational culture have seen greater progress.
Our found that 60% of organizations are adopting sustainability to align with the demands of potential employees.

•  Sustainable software architecture 

Sustainability needs to be at the very center of an organization’s business. While emissions and output need to be carefully scrutinized, developing a sustainable software architecture is an imperative.  

Understanding the environmental consequences of software deployment and making decisions based on the carbon cost of infrastructure will ingrain sustainability into the foundations of an enterprise. Once the architecture is available, specific software modules within the structural design must be viewed from a sustainability perspective. For instance, organizations should empower their developers to understand the carbon cost of their software modules and use green coding to produce algorithms that have minimal energy consumption, at all times.

Upskilling developers in circular design will help product and design teams lessen their waste and thus their environmental footprints.

Sustainable IT can play a critical role in creating a circular economy by reducing waste, maximizing resource efficiency, and promoting more sustainable production and consumption practices. By introducing sustainability into the company’s value chain, you will drive the whole organization toward new efficiencies and a circular economy.

Moving forward, sustainability must be at the core of all our efforts. While many organizations have begun to focus on their overall sustainability agenda, the critical issue of sustainable IT has been overlooked. To give sustainable IT the attention it deserves, organizations need to understand the carbon cost of our digital world and accelerate the move to sustainable systems with engaged and dedicated teams. In this way, sustainable IT can play a central part in tackling climate change, promoting a circular economy, driving innovation, and moving the world to a more resilient and sustainable future.