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Does your AI system know what happened the last time it made a mistake? Can it distinguish which completions led to success, which failed, and why? If not, the issue might not be your model. It might be your logging policy. If you’re building, let’s talk Whether you’re designing R&D copilots, regulatory-aware assistants, or adaptive fraud engines — if you’re wondering how to make them learn without crossing compliance lines, I’ve helped teams solve that. From architectural reviews to reinforcement tuning, I’d be happy to share what’s worked — and help you build systems that get better every day. Because real AI doesn’t just generate — it evolves. This article is published as part of the Foundry Expert Contributor Network.Want to join? source

Agentic AI and shifts in persona experiences made S/4HANA migration more critical for PwC Over the last seven years, PwC has made significant investments in digital transformation. Our business urgency was driven by the need to scale global delivery, reimagine operations to manage costs, and empower our people with powerful digital experiences. The firm made significant investments and innovations in cloud, advanced analytics, and GenAI. But we recognized that modernizing our ERP core was a foundational dependency to applying these technologies to our operations, and to achieving the global, cost, and experience objectives.  We learned that traditional ROI methods for S/4HANA migration don’t always yield figures that will impress a CFO. Licensing and implementation costs stack up high relative to value from conventional process improvements from new functionality. But considering the technology suite – centered on the resilient S/4HANA applications and extended by new technologies and cloud services – the potential emerges for ERP to become a modern ERP core. And a modern ERP core is key to unlocking the next wave of automation and intelligence in business operations. PwC recognized that future-proof business systems should enable four digital pillars – each representing a shift in how users will interact with business systems and data: PwC To enable these pillars across our technological ecosystem, our ERP stack needed to be more modern and more digital. So, we evolved our view of what a digital core must include. What are the elements of a modern ERP that can make it a valuable foundation for an intelligent enterprise? Here are the elements we have applied at PwC and are helping our clients apply: PwC These are all critical elements. Without them, it becomes significantly harder to build reliable, agentic AI for business processes that include ERP functionality or data. They also combine to make intelligence possible. To predict financial performance, for example, data must become more reliable at the source, as it’s transacted and classified. Maintaining reliable data at the source has traditionally been difficult for humans, but automations and co-pilots will help. It is still important to develop a set of business improvement targets that can be traced to new functionality and process simplifications. It’s necessary for leadership approval and useful in motivating functional managers to help drive the program. But effective modernization should also aim to deliver these integral features that establish ERP as a foundational enabler for the four digital pillars. This is the digital core imperative. The PwC global network now has multiple territories live on S/4HANA and is adding more sites quickly. We have digitally mapped each business process, deployed global standard data models, extended the solution with our own cloud-native creations (winning an unprecedented three SAP innovation awards in a row), and began testing how to use SAP applications with a conversational AI experience. Achieving a digital core – combined with the lessons from our own transformation journey- has become a pivotal lens through which we can now guide clients. So, hold on to your seats – we’re launching the next generation of business applications, and we’re just beginning to see how far this can take our firm and our clients. We built for what’s next, so you can get there now. Learn more about PwC’s cloud journey, view system demonstrations, or discuss how to build the architectural imperatives into your enterprise’s S/4HANA migration. Jose RochaPrincipal SAP Solution Studio [email protected] Mark ShieldsPrincipalSAP AI [email protected] Karina HennebergerDirectorSAP Cloud Program [email protected] source

“One of the toughest challenges in agentic systems today is turning messy, unstructured inputs into clean, organized task flows. Salesforce already has Einstein for predictions and the CRM graph for data. What they didn’t have was a way to take, say, a supplier contract PDF or an email about a delayed shipment and instantly spin it into an actionable, multi-step workflow. That’s Regrello’s strength,” Mistry said. Forrester VP and principal analyst Charlie Dai sees Regrello’s integration into Agentforce as a way for Salesforce to augment its agentic AI capabilities with automated, domain knowledge-driven workflows. “It aligns with Salesforce’s strategy to embed AI agents across business functions and will likely to boost autonomy in targeting operations like inventory management, predictive maintenance, and supply chain coordination,” Dai said. source

In a move that aims to improve accessibility for agentic AI, Salesforce on Tuesday announced new payment options for its autonomous AI agent suite, Agentforce. The new options, built on the flexible pricing the company introduced in May, allow customers to use Flex Credits to pay for the actions agents take, like updating customer records or automating workflows. Going forward, Agentforce customers will choose from three billing models. The pay-as-you-go option is paying monthly for Flex Credits used and has no upfront commitment. Pre-commit is agreeing upfront to buy a certain number of Flex Credits in exchange for more favorable pricing, and paying monthly. Savings scale, too, with commitment to this option. And the third is pre-purchase, which is paying upfront to save the most and is directed at customers with predictable and consistent usage. source

The maxim “English is the new programming language” has become a reality in enterprise software. With the rise of natural language processing and artificial intelligence (AI) copilots, what the industry has always known as “coding” is now a thing of the past. Today, ideas and intent drive development. But something got lost along the way to this new paradigm—integration. Historically, organizations have installed and managed software platforms across their enterprises and followed those deployments with point upgrades, new modules, and complementary tools, all of which helped advance the platforms and improve business performance. But that’s not always the case when adopting AI-powered tools, like copilots, low-code tools, and domain-specific AI tools. The reality is that all too often AI tools often fail to deliver ROI because organizations chase speed without redesigning processes, addressing blockers, upskilling talent, or capturing the telemetry needed to measure impact. As a result, the promised impact of the tools never materializes, and ROI remains elusive. As developers across industries scramble to crack the code of harmonious and smarter tools integration, Hitachi has taken a novel, if not counter-intuitive approach to the problem. Rather than develop yet more software to run atop platforms, it attacked it at the root level—specifically, the software development lifecycle (SDLC) level—and changed forever the way organizations would view SDLC. A new way to conduct orchestration To help understand current approaches to orchestration, Suhail Khaki, Chief Technology Officer, Software Development Lifecycle (SDLC) at GlobalLogic, a Hitachi Group company, likens it to autonomous driving. “With a Tesla, for example, you enter an address and drive yourself, only engaging ‘Autopilot’ in certain conditions, such as when there’s traffic or a straight road and you want to relax,” Khaki said. “In that mode, the human takes you from point A to point B, using the vehicle as a tool.” In this scenario, humans orchestrate every handoff. Even modern SDLC management methods like Agile still depend on handoffs between stages, which can represent 10% to 20% of total development flow. As the latency builds, everything slows. But when Tesla’s ‘Full Self-Driving (FSD)’ capability is engaged, the car takes you to the destination autonomously, alerting the person only when it encounters a situation that requires human intervention. “That is how I see the future of AI-driven software development lifecycles: an AI that orchestrates and controls the stages end-to-end, engaging humans only when necessary,” Khaki said. Injecting velocity into the equation This primary focus for speed led to the development of VelocityAI, which boasts AI-driven orchestration and enriched context and telemetry as core SDLC capabilities. With the platform, intelligent agents manage the flow between requirements, development, testing, and deployment. And all of it is based on intent and context, rather than rigid process gates. In addition, intent-based routing and semantic prioritization determines what needs to be done, and in what order, based on the user’s goals. “You tell it to build requirements, and it pulls in relevant system, domain, and project data to generate your backlog automatically,” according to Raj Sethi, Senior Vice President of Technology, also at GlobalLogic. “This is done while orchestrating between product owner, business analysts, quality engineers, architects and engineers to groom the backlog into ready state.” At the core of this approach is a context-aware knowledge engine—designed for the specific needs of industries like healthcare, automotive, and telecommunications. “Context is extremely important,” Sethi says. “Without it, I don’t care how smart you are, you can’t solve the problem.” Rather than giving developers a blank canvas, the system provides rich context. “It’s like proofreading with wiggly lines for spelling and red lines for grammar versus checking every word yourself,” Sethi says. “It’s a big difference.” When software interfaces with machinery Make no mistake, enterprises are rife with AI tool-related challenges. Whether it’s the lack of integration capabilities, the influx of shadow AI, where employees download tools without IT approval, or the general lack of risk evaluation, the technology is wreaking havoc. In late 2023, the MIT Sloan Management Review and Boston Consulting Group published a report that surveyed 1,240 across 59 industries in 87 countries and found that third-party AI tools were responsible for more than 55% of AI-related failures in organizations. Industrial settings, however, where mission-critical systems across energy, transportation, and manufacturing, can’t tolerate such risks. The VelocityAI approach to orchestration is designed for just such industrial environments, where software must interface with physical machinery, sensors, and real-world operations. Through its AI-driven orchestration, the platform aims to automatically enforce compliance, though implementation complexity varies. In other words, when developers describe requirements in natural language, the platform applies relevant regulations—like HIPAA or automotive safety standards—without being told. “AI now interprets requirements in the context of compliance, reducing the need for manual review,” Khaki says. “One domain expert can now validate what used to take five experts.” Speeding development, reducing latency Hitachi’s GlobalLogic recently modernized and enhanced a legacy promotions system for a client’s fleet rental and management platform using the building blocks of VelocityAI. That legacy system, which required coding changes for even simple promotions, was originally developed using outdated J2EE technology with a database on AS400.  The project was completed and went into production in only six months, a pace that wouldn’t have been possible with traditional methods, Sethi says. The system has also been enhanced to support repair systems that visually identify vehicle models and guide technicians through repairs step-by-step. In addition, video analysis systems have been included to autonomously track vehicles and evaluate damage without needing additional specialized hardware. Today, VelocityAI is being extended into a range of industries, including telecom, automotive, and device-testing sectors. The real impact, however, goes beyond speed; this new approach—AI-infused SDLC—also allows teams to rapidly experiment with ideas and discover what works. “You can now test and verify an idea in hours, something that was impossible before,” Khaki says. “Solving the orchestration challenge could unlock an AI impact on par with the computer revolution—driving adoption, experimentation, and innovation at scale.” ____________ GlobalLogic is a Hitachi Group company that provides experience design, engineering,

Yeah, great question. And, you know, we get asked, Are we disrupting other people’s you know, work by rolling out these solutions, right? And my answer always is, we’re not only, you know, transforming business in in the operational aspects or the education or the research aspect, we’re also disrupting and transforming how we do software development. So we’re to the point you were asking absolutely yes, you know, I think about a year and a half ago itself, we made it available to pretty much everybody on the team. You know, name the popular tools the teams are using those capabilities, and we do see benefits, right? I think again on the maturity curve where we can use these capabilities. I think again, if you play with this stuff, you learn where you can use it effectively. And you can also see the trend lines of where you think you could use them in a few years, or, you know, in some cases, even a quarter or two later. And so we are using it across the care, you know, across all of software development. And we definitely see advantages. Sometimes advantages are more in taking away the grunt work a software engineer has to do, yeah, that’s just hugely impactful. There’s just like we talked about the joy of practice of physicians. You know, when we roll out these tools, we want them to spend more time with the patients, rather than, you know, spending time documenting stuff, which is kind of what we’ve done when we rolled out ambient listening. So now a physician just talks to a patient and you know, the documentation automatically happens for them. Similarly, aspects of rolling out these capabilities for software engineers also brings back the joy of doing what we got into the business of doing in the first place. You know, just writing a routine and having it automatically create a lot of test cases around it, that’s a huge, you know, impact, right? Yeah, we as software engineers were always able to imagine what the system would do, but we also knew it would take a certain amount of time. If we had the right processes, we were making sure it was secure. We were doing all the right software design life cycle, you know, steps, yeah, yeah. Can it do all of it in a really complex ecosystem? No, but can it help in individual steps, and, you know, help speed those individual things up Absolutely. And we are seeing all of that. source

As the world accelerates towards the AI era, business leaders across the Middle East, Turkey, and Africa (META) are rethinking their transformation strategies. Increasingly, businesses are shifting to intelligent business regeneration, where digital is no longer an enabler but the foundation of the enterprise. This shift is reshaping industries, with companies deploying technology at scale, building platform-based models, and generating substantial revenue from digital streams. According to IDC research, 68% of organisations in META already identify as digital businesses, with 28% of their revenue coming from digital business models. That figure is projected to rise to 44% in the coming years, signaling a decisive shift from product-based to platform-enabled business models.1 From direct-to-consumer offerings and dynamic pricing to API monetisation and industry ecosystems, businesses are rewriting the rules of value creation. The challenge: Regenerating amid disruption Transformation at this scale brings complexity. Despite their ambitions, organisations face several roadblocks on the path to tech-driven business regeneration. These challenges typically fall into four broad categories: strategy, skills, systems, and data. The most pressing issue is the absence of a unified, enterprise-wide digital strategy. Many businesses struggle with limited executive ownership, fragmented planning, and resistance to change. IDC research shows that 64% of organisations in META have disconnected or poorly aligned digital strategies, undermining the impact of their transformation efforts.1 A second major hurdle is the shortage of digital and technical skills. The talent gap is fueled by brain drain and outdated training programs that fail to keep up with the pace of innovation. Legacy IT systems present another significant barrier. Many enterprises continue to rely on ageing infrastructure due to conservative mindsets, continuity concerns, and employee reluctance to adopt new tools. Finally, a lack of high-quality, accessible data hampers innovation. Siloed departments, fragmented IT systems, and weak data governance contribute to poor data quality and low organisational data literacy. Best practices: Building a future-ready business Organisations must adopt a proactive, tech-driven approach to overcome these challenges and thrive in a digital-first world. Here are three best practices to guide the way: Embrace intelligent business regeneration: Digital experiences are no longer optional; they’re expected by customers, employees, partners, and suppliers alike. To remain competitive, businesses must go beyond surface-level digitisation. They must build new digital revenue streams while optimising internal operations to reduce costs, boost efficiency, and increase resilience. Anchor regeneration in a unified digital strategy: Develop a comprehensive digital roadmap that aligns with corporate strategy. Clearly define roles, responsibilities, and governance structures, especially across the C-suite. Regularly measure progress using digital KPIs and keep the strategy agile, ready to evolve with market conditions. Lay the foundation with a platform-based technology architecture: Leading digital businesses are moving towards a digital business platform approach. This model emphasises experience-centric technologies, intelligent platforms, modular architectures, agile development, cloud-native design, and secure environments. Such an integrated architecture enables organisations to automate workflows, scale AI-driven capabilities, and make faster, smarter decisions using real-time data. Transformation is no longer a one-time initiative but a continuous journey of regeneration that touches every part of the business. In the AI era, success will belong to those who can combine strategic vision with agile execution, underpinned by modern architecture, empowered talent, and intelligent use of data. By addressing the foundational challenges and embracing a holistic, tech-driven approach, organisations can future-proof themselves and unlock new sources of growth, innovation, and value in an increasingly digital world. Explore how leading organisations are aligning platforms, people, and priorities to scale with confidence by downloading the “Intelligent Regeneration: A Guide to Thriving in the AI Era” eBook.  1 Source: IDC Digital Executive Sentiment Survey 2024 (META, N=498). 250+ employees only. source

The cybersecurity sector entered the year facing three converging factors, creating a “perfect storm” that challenges our national cybersecurity. The first element, cybercrime, continues to spread at unprecedented speed: 2025 opened with a 44% year-over-year surge in cyberattacks, with the cost of cybercrime projected to reach $10.5 trillion by 2029. AI is the second element, exponentially improving attackers’ ability to impersonate, reduce costs and evade detection. The third — and probably the least expected — is the recent shifts in cybersecurity leadership and policy, eliminating many aspects of our existing cybersecurity programs and personnel. Our modern economy depends on interconnected networks spanning global supply chains, military and critical infrastructure, the power grid, healthcare and election systems and financial institutions. When these systems are disrupted, the impact can debilitate national security, economic stability, public health and safety. The weakening of one link threatens the stability and security of the entire system. The interconnective nature of these distributed platforms demands a transparent and predictable set of rules and protections to ensure a stable and secure ecosystem. It wasn’t supposed to be this way  The first Trump administration implemented and supported robust cybersecurity efforts, leading to expectations of a stronger, not weaker, set of policies and programs. Much to the surprise of the security community, the fiscal 2026 budget proposal reduces CISA funding by $135 million. While budget fluctuations are not new, including larger cuts proposed during a prior administration, the cybersecurity community has expressed concern over the timing of this reduction amid escalating threats. This follows executive orders that have revoked Biden-era AI safety policies and disbanded the Cyber Safety Review Board (CSRB), while modifying other cybersecurity initiatives. Putting aside the merits of reform or evolving our security stance, it is the suddenness and lack of coordination that create uncertainty and potential gaps in our security stance.  source

Given the strong reliance on fossil fuels like coal, oil, and gas, the growth of the global economy has led to increased greenhouse gas emissions, particularly carbon dioxide (CO₂). The concentration of carbon dioxide in the atmosphere is now more than 50% higher than pre-industrial levels and is increasing at record speeds. As a result, the world is increasingly encountering intense droughts, water scarcity, destructive fires, rising sea levels, flooding, melting polar ice, catastrophic storms, and declining biodiversity. Against this backdrop, determining how to balance economic growth, energy security, and environmental protection has become a worldwide problem. In the meantime, sustainability challenges have significant social impacts, including forced migration, unequal distribution of essential resources, widening inequality, and growing public health issues. Becoming a mandate rather than a choice, sustainability has become essential for ensuring the well-being of future generations, preserving our planet’s resources, and fostering a balanced relationship between economic growth, environmental protection, and social equity. Sustainability is seen as a crucial responsibility Developing a green, low-carbon, sustainable society is an obligation all governments and industry leaders must shoulder, and green transformation provides an opportunity that must be seized without delay. By integrating sustainability, enterprises not only contribute to a healthier planet but also position themselves for long-term success by reducing operational costs, enhancing their reputation, fostering loyalty among environmentally conscious customers, and encouraging innovation. Additionally, governments can guide societies toward a sustainable future by taking a proactive and collaborative approach. Enterprises can scale sustainability by embedding it into their core business strategies and operations while leveraging innovation, collaboration, and leadership. On the other hand, addressing sustainability challenges requires a holistic approach that considers not just environmental and economic factors but also the social implications and needs of diverse populations. In parallel with this imperative, the corporate sustainability landscape is evolving: targets that were set over the past years need to be tied to feasible strategies; environmental, social, and governance (ESG) materiality remains dynamic and requires organisations to consider new topic areas; and the regulatory landscape is tightening. According to IDC’s Worldwide CEO Survey 2024, meeting ESG goals and requirements has emerged as the top business priority for CEOs in 2024. However, since sustainability transformation is often more complex than initially anticipated, it must be viewed as a marathon rather than a sprint. While sustainability transformation is gaining strong traction across the Middle East, Türkiye, and Africa (META), many organisations are still in the initial stages of sustainability maturity. How sustainability creates business value Forward-looking organisations see an opportunity to leverage their sustainability initiatives as a way to create business value. This requires embedding sustainability data into existing operations so it becomes a factor in business decisions, much like cost considerations. As this becomes more common in organisations, functional leads will take greater responsibility for meeting sustainability objectives in their respective areas, and the CSO role will become more of an orchestrator of sustainability activities across the organisation. According to IDC FutureScape: Worldwide Sustainability/ESG 2024 Predictions, companies that are most advanced in terms of sustainable business transformation (~10–20%) will have sustainability embedded across their organisations, with CSOs only having a coordination role. Technologies for sustainability, often integrated with smart systems and innovative practices, play a crucial role in addressing global environmental challenges. Renewable energy technologies harness energy from natural processes that are continually replenished. These technologies aim to reduce reliance on fossil fuels, decrease greenhouse gas emissions, and promote sustainable energy. Energy efficiency technologies are designed to use less energy while delivering the same or improved level of service. These technologies not only lower energy consumption but also reduce costs and greenhouse gas emissions, contributing to sustainability. Sustainable transportation technologies aim to reduce environmental impact and enhance efficiency in the movement of people and goods. These technologies collectively contribute to reducing greenhouse gas emissions, enhancing energy efficiency, and promoting a more sustainable transportation ecosystem. Waste management and recycling technologies focus on minimising waste, maximising resource recovery, and reducing environmental impact. These technologies are integral to creating more sustainable waste management practices, reducing landfill use, and promoting a circular economy. How to get started Implementing sustainability in business is not just an ethical choice; it is a strategic approach that aligns with market trends, regulatory demands, and consumer expectations, ultimately leading to long-term success and resilience. It involves integrating environmentally and socially responsible practices into operations, culture, and strategy. By embedding sustainability into the core of business, organisations can create long-term value, reduce environmental impact and improve community relations while meeting the growing expectations of customers and investors. Organisations need a comprehensive sustainability strategy that outlines how an organisation will integrate sustainable practices into its operations, culture, and decision-making processes. Almost all the organisations that responded to IDC’s Worldwide Sustainability Readiness Survey 2024 now recognise sustainability as a strategic priority. Such a strategy should balance environmental, social, and economic goals, ensuring long-term viability while addressing the needs of stakeholders and the planet. Developing a sustainability strategy involves a structured approach that aligns with an organisation’s values and goals. The future of sustainability is full of opportunities for innovation, economic growth, and societal transformation. Organisations that invest in green technology, promote resource efficiency, and develop solutions for climate resilience will be well-positioned to thrive in a sustainability-focused world. As consumers, investors, and regulators increasingly prioritise sustainability, these opportunities represent not only growth potential but also a pathway to a more sustainable and equitable global economy. Learn how to unlock the business value of sustainability when you download this eBook, “Towards a Progressive Future: Unleashing the Power of Sustainability”.  source