In this episode of HFS Unfiltered Stories, Divya Iyer, Practice Leader at HFS Research, is joined by Tom Scazzafavo, Global Financial Crime Managed Services Leader, EY, for a candid look at why financial crime compliance keeps failing to deliver, and how AI is changing the equation. The conversation follows EY's recognition as a Horizon 3 Market Leader in the HFS Horizons Financial Crime Compliance Services 2026 report. Tom's diagnosis is pointed: institutions have poured money into compliance for over a decade, yet enforcement actions haven’t fallen, because the investment was incremental rather than transformational. Firms layered new tech on fragmented processes, legacy systems, and inconsistent data, so spending rose while the operating model never changed. He traces it to three root causes: data trapped in silos, inefficient manual processes, and incentives that reward throughput over real risk reduction. Tom is clear-eyed about AI's reality, too, separating where it genuinely works today (alert reduction, entity resolution, and network analytics, and generative AI that speeds investigations) from where ambition outruns reality (fully autonomous decisioning and scaling across jurisdictions). His verdict: AI is powerful, but it's no silver bullet, and humans stay in the loop for a while yet. He shares EY's “AI trust and governance” approach, treating each agent like a customer in a KYC process, and closes with a sharp look ahead: criminals adopting AI as fast as institutions through synthetic identities and deepfakes, the rise of real-time payments and digital assets, and widening cross-border regulatory divergence. The through-line: financial crime is becoming faster and more networked, and the winners will be those who move to real-time, intelligence-led compliance.Learn more about the 2026 HFS Horizons: Financial Crime Compliance (FCC) in Financial Services - covering 15 providers: https://www.hfsresearch.com/research/hfs-horizons-financial-crime-compliance-fcc-in-financial-services-2026/

In this episode of HFS Unfiltered Stories, Saurabh Gupta, President at HFS Research, is joined by Ramesh Gopalan, Group CEO & Managing Director of Sagility, to discuss how AI can tackle the trillion-dollar inefficiencies in US healthcare. They discuss why traditional BPO models have reached their limits, why AI pilots often fail to scale, and why simply automating broken processes won't deliver meaningful results. Ramesh explains Sagility's Synchrony platform and how a services-as-software approach orchestrates end-to-end healthcare workflows, combining AI, domain expertise, and human oversight. The conversation explores the shift from activity-based to outcome-based pricing, how healthcare organizations can reduce costs while improving revenue and compliance, and why domain expertise becomes even more valuable in an AI-driven world. Ramesh also shares his vision of agentic AI orchestrating the majority of healthcare workflows within the next three to five years.#ServicesAsSoftware #HealthcareAI #AgenticAI #HealthcareBPO #Sagility #HFSResearch #PayerOperations #PriorAuthorization #OutcomeBasedPricing #DigitalTransformation

Join Achyuta Ghosh and Steve Rudderham for a conversation on how GBS is being rebuilt as a true engine of enterprise value, not just a scaled shared services function. They discuss how Ecolab’s “One Ecolab” strategy is reshaping GBS around nine end-to-end processes, why cost and SLAs are now table stakes rather than differentiators, and how data, AI, and talent are coming together to move the needle on customer experience, growth, and enterprise decision-making. What you’ll hear: Why the traditional shared services playbook is running out of runway, and how Ecolab is positioning GBS as the connector across process, data, people, and technology. Steve draws on 15 years across Kellogg, AkzoNobel, Carrier, and his early BPO days at GECIS, and shares what he is doing three months into leading GBS at Ecolab.Key takeaways: Why cost per transaction and SLAs are table stakes, and what enterprise KPIs GBS should actually be moving. How Ecolab has organized the enterprise into nine end-to-end processes, with GBS acting as the connector between functions and geographies. How a lead-to-cash view, applied to the top 35 clients, is helping GBS improve customer experience and free up commercial time. The data-first agenda: moving customer, vendor, and financial master data from a byproduct into a true enterprise asset before scaling AI. A real example of how collecting data changed the team's prioritization of customer calls and freed capacity for higher-value work. Why running fast on AI without fixing data governance and process consistency is a common mistake, and how Ecolab is sequencing that work. The talent shift: reskilling every associate on AI and automation basics, while bringing in specialized talent in advanced analytics and AI. Why the gap between leading and lagging GBS organizations is going to widen, and what separates the two three years from now.To know more about HFS on Global Capability Centers (GCCs), visit us here: https://www.hfsresearch.com/global-capability-centers-gccs/

Join Achyuta Ghosh and Mohit Bhatia for a candid conversation on what it takes to build a strategic GCC from an early stage, at a time when the old playbook no longer applies. They discuss why the answer is not to jump straight into AI, why fixing the basics still matters, how Rolls-Royce is thinking about data, talent, and enterprise outcomes, and what India means as a home market for a company known globally for jet engines, propulsion, and energy. What you'll hear: Why an early-stage GCC in 2026 does not need to follow the four-stage transformation curve that GCCs went through 20 years ago, and where it can leapfrog straight to modern platforms. Mohit draws on nearly four decades across Maersk, Mondelez, Genpact, and American Express, and shares how he is applying that experience at Rolls-Royce without falling back on the traditional playbook.Key takeaways: Why the first 12 to 18 months of a new GCC are still about execution excellence and fixing the basics, before piling on modern tech and AI. How to "jump the curve" and start at the top of someone else's S-curve, rather than repeating three decades of legacy build-outs. Why AI should sit in the fabric of processes, not as a set of pilots or point solutions bolted on the side.The data-first agenda: cleaning, safeguarding, and segregating data before expecting AI to produce ROI.How Mohit is thinking about services-as-software and why the shift will be gradual, not overnight, until the ecosystem catches up on data integrity and end-to-end processes. The build versus buy call: keeping core GCC execution internal while partnering with third parties on ERP, workflow tools, and system integration. Where AI actually pays off at Rolls-Royce, from predictive analytics on jet engine maintenance to three-way match, auto-reconciliations, and employee self-service. The talent shift: hiring for curiosity, learning agility, enterprise leader mindset, and tech comfort, without discounting people management, empathetic leadership, and domain expertise.Why Rolls-Royce is treating India as a home market, and what the ecosystem could look like at 10,000 people over the next five to seven years.To know more about HFS on Global Capability Centers (GCCs), visit us here: https://www.hfsresearch.com/global-capability-centers-gccs/

In this episode of HFS Unfiltered Stories, Saurabh Gupta, President of HFS Research, sits down with Shveta Arora, SVP & Global Head of Consulting at Cognizant, for a candid conversation about one of the most contested questions in enterprise tech right now: what does AI actually do to consulting? The consensus fear is that AI hollows out consulting. Shveta makes the opposite case, there will be more consulting because of AI, not less, and walks through the structural shifts already reshaping how the work gets delivered. Consultants are moving beyond “slideware” to vibe-code show-and-tell prototypes and working proofs of concept. Agentic transformations now demand consulting and domain expertise embedded across the entire lifecycle, not just the front end, but through build (context engineering, ontology engineering) and into run, where agent performance is continuously improved after deployment. Saurabh and Shveta dig into the model makers, Anthropic, OpenAI, and others — moving into the services market, and why Shveta sees that as the biggest possible endorsement of how valuable services are. They unpack Cognizant's concept of the “AI velocity gap”, the distance between raw model capability and the enterprise value clients can realize, and why services are the only way to close it. The conversation also brings HFS Research's “services-as-software” thesis to life, with customer service and high-volume processes like payroll and accounts payable as concrete examples of agent-run, human-managed delivery. Finally, the two tackle the hardest unsolved problems: enterprise “talent debt” (which Shveta argues leaders should tackle before technology debt), bottom-up innovation as the way to bring employees along, the broken economics of buying AI-enabled services when rate cards and token-based pricing both fall short, and how her own leadership style is shifting toward a hands-on “player coach” model. A sharp, fast-moving discussion for anyone navigating the future of consulting, BPO, and enterprise AI.

In this episode of HFS Unfiltered Stories, Ashwin Venkatesan, Executive Research Leader at HFS Research, sat down with Pandiya Kumar Rajamony, Executive Vice President at LTM, to discuss one of the hottest topics in enterprise tech today: how AI is fundamentally rewiring infrastructure services.Following HFS Research's Horizons report on next-generation infrastructure services, where LTM was positioned as a Horizon 3 provider, this conversation digs into why infrastructure has shifted from simply hosting workloads to becoming the intelligent control plane for enterprise AI. Pandi explains why the question is no longer “Can my infrastructure run AI?” but rather “Can my infrastructure help me scale AI safely, efficiently, and intelligently?” The discussion covers the four forces reshaping enterprise infrastructure expectations: AI-aware infrastructure (since training and inference behave very differently), dynamic workload placement across cloud, data center, and edge, security and governance in the age of AI agents, and the rising cost pressure of GPU infrastructure and tokenization. Pand also tackles data and infrastructure sovereignty, the move toward heterogeneous CPU-plus-GPU workloads, and why true AI-native operations can't be achieved by simply layering automation onto existing processes. You'll also hear how LTM's cognitive infrastructure services strategy comes to life through its BlueVerse platform, BlueVerse Knowledge Fabric, and the IRUN agentic operating model: including two real client stories: modernizing India's tax analytics platform for the Central Board of Direct Taxes (Insight 2.0), delivering the same performance with a 37% lower GPU footprint, and an IRUN super-agent deployment for a long-standing travel client that cut operational costs by 35% while doubling engagement revenue. Learn more about the 2026 HFS Next-gen IT Infrastructure Services report - covering 17 service providers: https://www.hfsresearch.com/research/hfs-horizons-next-gen-it-infrastructure-services-2026/

In this episode of Unfiltered Stories, Saurabh Gupta sits down with Rory Fidler, CIO at Menzies Aviation, and Sorabh Singhal from Wipro to talk about a challenge every enterprise is facing right now, modernization that never seems to end.This videocast is divided into three episodes. Watch all three to hear the complete conversation and explore the key insights on AI and legacy modernization.Episode 1: Unfiltered Stories | How AI enables a platform-based approach to enterprise modernization - Why modernization never endsEnterprise modernization has been underway for years, yet most organizations still feel stuck. Now, with AI accelerating the urgency, leaders are caught between pressure to move fast and fatigue from past efforts. In this episode, we explore why modernization programs often succeed on paper but fail to deliver real impact, and why AI is making this challenge even more critical. What you’ll hearThe reality of AI hype vs fear on the groundWhy modernization feels like a never-ending cycleThe disconnect between reported success and real outcomesWhy “bolt-on” approaches failWatch Part 2 to see how leading enterprises are breaking out of this cycle with a platform-based approach.Episode 2: Unfiltered Stories | How AI enables a platform-based approach to enterprise modernization - From projects to platformsModernization doesn’t work when treated as isolated projects. It works when reimagined as a platform-driven transformation. In this episode, we explore how organizations are moving from fragmented systems to platform-based architectures, and why this shift is critical before AI can deliver real value. What you’ll hearThe real role of AI in modernizationWhy most enterprises get stuck in pilot modeA real-world example of platform-led transformationWhy data becomes the foundation for AIWatch Part 3 to understand how AI turns modernization into a continuous, value-driving capability. Episode 3: Unfiltered Stories | How AI enables a platform-based approach to enterprise modernization - From modernization to business value Modernization is no longer just about upgrading systems. It’s about enabling continuous transformation and business growth. In this final episode, we explore how AI builds on platform foundations to unlock new value, drive innovation, and reshape how enterprises operate. What you’ll hearWhy modernization must become continuousHow AI connects systems into a “thread of gold.”What real business value from AI looks likePractical advice for CIOs to get startedWatch the full series to see how enterprises are rethinking modernization for the AI era, and what it takes to make it work in practice. Read the full report "Legacy modernization is a competitiveness issue, and CIOs must own the fix," here.

Join Achyuta Ghosh and Arvind Vaishnav for a conversation on how a healthcare GCC creates real impact for patients and clinicians, and what it takes for a center to move from running functions to shaping enterprise outcomes. They discuss how the Philips Innovation Campus is building AI-led solutions that cut MRI scan times in half, the talent shifts behind end-to-end value creation, and how partnerships with clinicians, academia, and startups are reshaping healthcare innovation from Bangalore. What you'll hear: Why the Philips Innovation Campus, with around 4,000 people and more than 30 years in Bangalore, is one of the largest healthcare innovation hubs in India, and what makes its work different from a traditional GCC. Arvind walks through real examples of how the campus delivers functional, economic, and social value, including SmartSpeed MRI, a homegrown AI capability that cuts scan time by 50 percent. Key takeaways: How a healthcare GCC measures impact through three lenses: functional value, economic value, and social value. A real example of bringing MRI scan time down from an hour to thirty minutes, and what that means for patients, clinicians, and access to care. Why end-to-end ownership of the clinician and patient journey is the new bar for healthcare GCCs. The talent shifts driving this change: clinical and product roles, quality and safety expertise, and digital skills like AI and cloud.The role of ecosystem partnerships with clinicians, academia, and startups in accelerating healthcare innovation. How AI is helping clinicians spend more time with patients, and less time with the technology. What is changing in how healthcare GCCs are expected to deliver, from supporting functions to shaping outcomes.To know more about HFS on Global Capability Centers (GCCs), visit us here: https://www.hfsresearch.com/global-capability-centers-gccs/

Join Achyuta Ghosh and Aparna Rao for a practical conversation on how AI is changing the actual work inside GCCs, and what that means for roles, skills, and leadership. They discuss how the GCC model is moving from processing tasks to making decisions, why AI cannot fix weak fundamentals, and what leaders need to do right now to stay relevant. What you'll hear: Why work in GCCs is no longer organized around steps and tasks. It is increasingly organized around decisions, and what humans should do versus what AI should do. Aparna draws on 25 years of building and scaling six GCCs across IT, retail, agriculture, pharma, and pharma logistics, and shares what is actually working on the ground at Cencora.Key takeaways: Why has work not reduced inside GCCs? It has elevated, and the bar for talent has risen with it. The three shifts reshaping GCC roles: from processing to judgment, from deep silos to T-shaped capability, and from doing the work to influencing how it gets done. Why does AI not fix weak fundamentals? It amplifies them, and what to do about that before you scale anything. Why is the right starting point not the tool, but the business problem, and how a recent hackathon at Cencora made that visible? How democratizing AI access, building AI governance into the capability framework, and investing in human learning together change what a GCC can deliver.Practical guidance for this quarter: redesign one or two high-impact workflows end-to-end rather than trying to transform everything at once. Why will the winners not be the GCCs that adopt AI the fastest, but the ones that use it most thoughtfully?To know more about HFS on Global Capability Centers (GCCs), visit us here: https://www.hfsresearch.com/global-capability-centers-gccs/

Join Achyuta Ghosh and Arindam Mukhopadhyay for a candid conversation on how leadership in Global Capability Centers must change. They talk about how the GCC model is moving past the old scale game and the "landlord" style of leadership, as AI reshapes how work gets done, how value is delivered, and what GCC leaders need to focus on next.What you'll hear: Why the biggest threat to the GCC model isn’t AI.It is leadership that has drifted away from domain expertise and process ownership, and what it takes to close that gap.Arindam draws on nearly two decades of building, scaling, transforming, and exiting GCCs across India, the Philippines, Malaysia, Poland, Hungary, Costa Rica, Ireland, and the US, and shares his view on what future-ready leadership looks like. Key takeaways:Why strong GCC growth numbers can mask real questions about long-term sustainability.The end of the "landlord" leadership role. • Managing facilities and headcount is no longer enough. Why the shift from scale-led to outcome-driven GCCs is a leadership problem first, and a technology problem second. The value of staying close to the process and demanding excellence from your team rather than just their time. How AI is reshaping the talent pyramid and the skills GCCs will need next. A practical test every leader can apply: start from the assumption that AI can do the work and rule it out only after kicking the tires hard. Why the next wave of GCC leaders will pivot from running large teams of people to leading a smaller core of rare, high-impact skills. The simple leadership mantra to carry forward: your job is to make your colleagues successful. To know more about HFS on Global Capability Centers (GCCs), visit us here.