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The task force suggested creating new standards, metrics, and definitions for energy use and efficiency metrics. Organizations should track and project data center power usage. Also, it said, the organizations that benefit the most from new infrastructure should bear the brunt of growing costs. Further, the electric grid must be modernized and secured, and AI can be used to enhance energy infrastructure, production, and efficiency. O’Connor detailed several more steps organizations can take that are “aligned with or supported by government recommendations.” In addition to simply using more energy-efficient hardware, some of these include: Optimizing models to reduce energy consumption, by model pruning, or removing redundant neurons from neural networks to reduce model size and computational load. Reducing the numerical precision of AI calculations through a technique known as quantization, which can result in up to 50% computational cost savings. Training a smaller model to replicate the behaviors of a larger model, reducing the need for extensive computational resources. Clear and practical or 273 pages too long? The extensive report also touches on other areas, including financial services, healthcare, data privacy, and R&D, and calls for federal preemption when it comes to AI — that is, federal law taking precedence over state law. source

Always on the cusp of technology innovation, the financial services industry (FSI) is once again poised for wholesale transformation, this time with Generative AI. Yet the complexity of what’s required highlights the need for partnerships and platforms calibrated to fast-track solutions at scale to capitalize on AI-era change. Financial institutions have an unprecedented opportunity to leverage AI/GenAI to expand services, drive massive productivity gains, mitigate risks, and reduce costs. Across financial services markets, GenAI can play a role in several areas, including: Optimizing product and service innovation Enhancing contact center interactions Delivering personalized banking experiences Modernizing code Detecting fraud Creating predictive analytics and forecasting for investment insights Empowering agent and advisors According to NVIDIA’s State of AI in Financial Services 2024 Trends report, 43% of respondents are already using GenAI in their organization. What’s more, three quarters consider their AI capabilities to be ahead of or right in line with their peers. More than half (51%) say they are confident that AI will be critical to their companies’ future success. GenAI-powered financial services use cases Across the sector, GenAI is empowering innovation and enabling new work patterns. Among them: Banking: Organizations are delivering personalized solutions with recommendations and enhancing customer service operations with avatar-assisted services and Natural Language Processing (NPL) chatbots that fulfill service requests promptly. GenAI is also helping to improve risk assessment via predictive analytics. In one example, BNY is deploying NVIDIA’s DGX SuperPOD AI supercomputer to enable AI-enabled applications, including deposit forecasting, payment automation, predictive trade analytics, and end-of-day cash balances. Trading: GenAI optimizes quant finance, helps refine trading strategies, executes trades more effectively, and revolutionizes capital markets forecasting. Using deep neural networks and Azure GPUs built with NVIDIA technology, startup Riskfuel is developing accelerated models based on AI to determine derivative valuation and risk sensitivity. GenAI can also play a role in report summarization as well as generate new trading opportunities to increase market returns. Payments: GenAI enables synthetic data generation and real-time fraud alerts for more proactive, accurate, and timely fraud monitoring. As new fraud patterns are identified, GenAI is used to create synthetic data and examples used to train enhanced fraud detection models. GenAI also helps identify patterns that assist in Suspicious Activity Report generation for anti-money laundering, greatly reducing investigation time. NVIDIA + Microsoft: Partnering for AI transformation at scale Given the pace of change, FSI companies need to lean into the right partnerships and resources to enable innovation. NVIDIA and Microsoft have a longstanding relationship centered on AI, and over the last two years, the pair have aligned GenAI offerings built from the ground up on Azure and the NVIDIA AI-enabled GPU stack. Microsoft’s Azure infrastructure and ecosystem of software tooling, including NVIDIA AI Enterprise, is tightly coupled with NVIDIA GPUs and networking to establish an AI-ready platform unmatched in performance, security, and resiliency. The NVIDIA DGX SuperPod is the fastest path to AI innovation at scale, delivering a full-stack, turnkey solution that eliminates design complexity and facilitates time to deployment.   The partners have a shared commitment to secure and responsible AI development, and experts and services are available to streamline capacity planning, provisioning, application performance testing, and user/DevOps training at each phase of the GenAI deployment cycle. The bottom line Microsoft and NVIDIA’s decades-long collaboration is unleashing a full spectrum of AI foundations and services that together will quick-start the AI revolution for financial services solutions. Read more from NVIDIA and Microsofthttps://blueprintforai.cio.com/ source

While this might be driving internal productivity, you also must think of it this way: As a distributor, at any one time, we deal with millions of parts. Our supplier partners keep sending us their price books, spec sheets and product information every quarter. So, having a group of people trying to go through all that data to find inaccuracies is a daunting, almost impossible, task.  But with AI and genAI capabilities, we can clean up any inaccuracies far more quickly than humans could. Sometimes within as little as 24 hours. That helps us improve our ability to convert and drive business through an improved experience for our customers.  Another AI example is our design services. We have a design hub that provides customers with self-service capabilities to create bot diagrams and turn them into spec sheets and part lists. With this tool, genAI allows customers to ask questions like, “Help me reduce the physical footprint by 30%” or “How do I drive my go-to-market timeline to three months shorter?” With the right data, the tool can incorporate these requests and create replacement specs, parts lists and suggestions. In this instance, incorporating genAI opens up a new, seamless experience we can offer the customer. source

Moreover, the subject matter of many prompts, some of which involved suicidal ideation and violence, among other disturbing topics, coupled with restrictions from Scale AI around break times and outside research, created a grueling, authoritarian workplace in which workers could be terminated for complaining about working conditions, payments, or company processes, the complaint said. Additionally, the suit says that McKinney and the many others in his position were misclassified under California law as independent contractors, rather than employees. Generally speaking, employers have fewer legal responsibilities to independent contractors than they have to full employees, who are more likely to be subject to state and federal laws about overtime payment, among other things. California’s legal standard for deciding which workers are independent contractors and which are employees is fairly strict, and is referred to as an ABC test, for its three-pronged nature. According to the California Labor and Workforce Development Agency, workers are employees unless they are free from the control and direction of the hiring entity, are doing work outside the usual course of the hiring entity’s business, and are “customarily engaged” in an independent business of the type they’re being hired for. None of those standards, the lawsuit argues, are met in the case of McKinney and the other Scale AI workers in his position. source

While initial work to fix data problems should be expected before an AI project, ongoing repair of data problems taking hours of staff time per day can be a warning sign that the organization’s data wasn’t ready for AI, Erolin adds. Organizations ready for AI should be able to automate some of the data management work, he says. “If you’re spending so much time to keep the lights on for operational side of data and cleansing, then you’re not utilizing your domain experts for larger strategic tasks,” he says. The legacy problem Legacy systems that collect and store limited data are part of the problem, says Rupert Brown, CTO and founder of Evidology Systems, a compliance solutions provider. In some industries, companies are using legacy software and middleware that aren’t designed to collect, transmit, and store data in ways modern AI models need, he adds. source

You’d be hard-pressed to find an SAP shop that doesn’t rely on customizations to fine-tune the enterprise platform for specific business processes or industry requirements. Rather than sticking with the out-of-the-box ERP system, many companies opt to modify the code for purposes such as: Creating unique billing reports to improve the customer paymen experience Establishing regulatory compliance processes for specific industries Implementing dashboards that aggregate data for more informed decision-making Developing specialized product tracking systems These customizations are often vital to business productivity and can give companies a competitive edge. It’s important to keep customizations running strong, even if they take some extra effort to maintain. According to a survey conducted by the American SAP User Group (ASUG) and Pillir, 91% of SAP users rely on custom code for essential business processes. Much of this code has been around for a while — 45% of survey respondents said they rely on custom code deployed six or more years ago. However, key personnel associated with custom code development and business logic are often no longer in the company’s employ. “Customizations are fantastic for differentiating business, more so than the vanilla SAP platform,” says Scott Hays, senior director of product marketing at Rimini Street, a provider of third-party enterprise software support and services. “That said, customizations might not always be documented well, resulting in a dependency on the people who wrote them. But they are important to the business and need to be treated like any other mission-critical code.” The third-party support advantage Complicating matters, ERP vendors typically don’t include customization support as part of their standard maintenance programs. To fill the gap, enterprises can turn to expensive external consultants, spend additional funding to hire more staff or somehow find and dedicate internal resources to support the custom code. Or, they can depend on an experienced third-party support provider with the proven expertise to tend to their important customizations. For nearly two decades, Rimini Street has simplified the complexity of IT, providing tailored support and expertise for mission-critical customizations as if they were part of the standard product — and at no additional charge. Such a partnership could ensure seamless, secure operations and ample maintenance handholding, even for heavily customized SAP environments. And services can be added to document customizations, eliminating the knowledge gap for good. “During the never-ending cycle of upgrades pushed by software vendors is where customizations are most likely to run into problems,” says Hays. “With Rimini Street, IT and finance leaders can maximize the potential of their existing systems while keeping their software running and fully compliant without upgrades, enabling them to benefit from the competitive advantage customizations provide.” Significant savings can lead to business growth Compared to the in-house costs for supporting customizations which can add 30% to 40% on top of the annual maintenance fees of ERP vendors, Rimini Street reduces SAP annual maintenance fees by up to 50% and dissolves the need for dedicated staffing for support. For Proton, Malaysia’s national car manufacturer, the switch from SAP support to Rimini Street yielded significant savings, contributing to the expansion of one of their plants to accommodate greater production volumes. “Many SAP customers around the globe choose Rimini Street because of the quality of our support, leading in the speed, scale and scope of our coverage,” says Hays. “We know and appreciate the importance of keeping customizations to differentiate their business from competitors. It’s all about growth, all about profitability, and Rimini Street is the proven partner that helps clients achieve both by leveraging their customized SAP platform.” To learn more about how Rimini Street can help you get a handle on your SAP customizations and free up IT time for more strategic endeavors, visit here. source

In IDC’s April 2024 CIO Poll Survey of 105 senior IT professionals and CIOs, “developing better IT governance and enterprise architecture” emerged as one of the top priorities for 2024, ranking fourth. While other priorities — including incorporating a focus on AI into the IT strategy, improving the approach to software sourcing and deployment, and building better IT skills and competencies — ranked higher in the survey, IT governance is much more foundational. Without well-functioning IT governance, how can you progress on competing priorities? It is fundamental for AI and essential for reducing cybersecurity risks or streamlining cloud migration processes, among other things. Additionally, CIOs indicate that the lack of alignment between IT and the business is their third biggest challenge within their organization (IDC’s CIO Sentiment Survey 2024, n = 395). Unfortunately, traditional governance models are proving insufficient to meet the dynamic demands of the digital or modern business environment as they were introduced to mostly enforce rules and regulations instead of shaping culture and bringing IT and business together. And alignment between IT and the business is still a challenge according to my conversations with CIOs today, and it has been for a long time. IT governance should facilitate how your organization’s culture shifts toward collaboration and focus on aligning how technology can accelerate and improve your organization’s products and services to delight customers and employees. The limitations of traditional IT governance models Historically, organizations have relied on three primary governance models: centralized, decentralized, and hybrid. While each model has its strengths, it also comes with significant limitations. Centralized governance often results in slower decision-making processes, as decisions are concentrated at the top levels, stifling agility. Decentralized governance, on the other hand, can lead to fragmented approaches and shadow IT, where departments independently adopt technologies without IT oversight. Hybrid governance attempts to balance control with flexibility, but it can still struggle to align IT initiatives with overarching business goals. The journey to digital business is not yet complete, with less than 38% of global organizations saying that digital is integrated or has transformed their organization, according to the CIO Sentiment Survey 2024. That leaves more than 50% of organizations with some work toward maturing their digital business. Also, the same survey shows that 33% of IT departments collaborate with other business units, but 67% are either collaborating ad hoc or making decisions with limited input from others — which does not improve the IT/business alignment agenda. Digital transformation requires alignment among all involved to deliver key initiatives with velocity and quality to key stakeholders such as customers, patients, or citizens. Pervasive IT governance can help, but it requires a shift in culture, which can start with IT and with you as the CIO. Embracing pervasive IT governance for greater business impact Pervasive IT governance is not just an evolution of existing models but a transformation in how organizations align technology with business strategy. It emphasizes a continuous feedback loop between IT and business units, enabling rapid adaptation to changing business needs. At its core, this approach focuses on collaborative governance, ensuring that decisions are made with input from across the organization, not just by or within the IT department. Key benefits of adopting pervasive IT governance include: Increased agility and innovation: By fostering continuous feedback and collaboration, IT and line-of-business (LOB) teams can quickly pivot to address emerging challenges. This model encourages innovation by empowering teams to experiment with new technologies. Balanced control and flexibility: Unlike rigid centralized models, pervasive governance allows organizations to maintain control over critical IT assets while granting teams the flexibility to innovate. Enhanced collaboration and buy-in: One of the cornerstones of pervasive IT governance is the establishment of strong relational mechanisms. These mechanisms are essential to build trust and buy-in toward achieving common objectives and goals. Implementing pervasive IT governance: Best practices for CIOs Shifting to a pervasive IT governance model is not without its challenges. The top three governance and compliance challenges we found in the CIO Sentiment Survey 2024 are support from LOB leaders (32%), support from the C-suite and board of directors (30.7%), and employee engagement (30.4%). This means that CIOs must rethink the structure, processes, and relationships within their organizations and in collaboration across the organization. Here are some best practices for CIOs looking to implement a pervasive IT governance approach: Establish clear roles and responsibilities: Use a RACI matrix to define the different responsible, accountable, consultative, and informative roles for the governance model, including IT, LOB, or other ecosystem partners. Foster continuous feedback loops: Continuous feedback refers to an ongoing mechanism for capturing, analyzing, and responding to different sentiments and input in real time related to an initiative or topic. During key change management initiatives (which are often part of an IT governance agenda), this approach enables leaders to monitor the impact of change as it happens, make data-driven adjustments, and foster a transparent, communicative environment that values different perspectives. It also motivates employee engagement and sets the tone for a responsive culture that adapts to evolving business needs. Leverage collaborative tools for transparency: While this might be the easiest and most obvious best practice, it is sometimes loaded with emotions as there are different collaborative tools in use, and people have their biases. The IDC MarketScape: Worldwide Team Collaboration Applications 2024 Vendor Assessment report (November 2024) provides some suggestions on tool vendors that are leaders in team collaboration. Focus on key performance indicators (KPIs) and continuous improvement: Assess your existing IT governance metrics and KPIs to see what you are measuring. While compliance, risk, resources, and performance metrics might already be there, look for metrics from which you could also derive KPIs for strategic alignment. Do remember that metrics and KPIs share similar traits, but the main difference is that a KPI is tied to a specific operational strategy, so be sure that you are tracking KPIs and not basic metrics that are lacking in necessary context to the business. The road ahead: Balancing risks and

She continues: “Some changes — like implementing gen AI — are fast to value. That’s where we need to implement, iterate, and improve quickly, while working toward our long-term strategies. Other changes can take more time, especially if they involve complex cross-functional work, significant investment, or upskilling.” Bobby Cameron, vice president and principal analyst at Forrester Research, says the length of IT roadmaps vary. Some IT organizations benefit from longer outlooks while others benefit from shorter ones depending on various factors, such as the pace of change in their industries, their organization’s objectives, and the projects and systems encompassed by a particular roadmap. But Cameron says research has found that the highest-performing IT organizations, which Forrester defines as transformational ones, have abandoned the three-year roadmap in favor of ones that are two years or less. And they’re refreshing their roadmaps at least quarterly to incorporate changes in the technology and business landscapes. source

InnoGames GmbH benefits from generative AI in several ways. Expert data engineer Volker Janz provides detailed insights into how this shapes the daily work processes at the gaming specialist. source

“Seamless customer experience includes multiple aspects – personalization, omnichannel strategy, customer journey mapping, and relationship building,” said Bhanushee Malhotra, practice director at Everest Group. “While utilizing AI for task automation and predictive insight generation is helpful to achieve seamless CX, there is a huge risk of AI being used to create highly convincing and personalized scams.” The role of conversational AI in the future of customer service The proliferation of GenAI in daily life is shifting customer behavior. Gartner’s research revealed that 45% of customers already use generative AI either personally or professionally. This growing reliance is expected to lead to 70% of customer service interactions being initiated — and resolved — through third-party AI assistants like Apple AI or Google Gemini by 2028, the report added. These assistants offer customers a more intuitive and low-effort experience compared to traditional service portals. Quinlan cautioned that companies must reevaluate their investments in self-service portals. source