HFS PODCASTS

What happens when a GCC moves beyond providing engineering capacity and starts owning the products, platforms, and capabilities that shape the company's future?

In this episode of the HFS GCC Advantage Videocast, Achyuta Ghosh of HFS Research speaks with Vivek Kadal of Esko about the evolution of Esko's India GCC and its growing role in the company's global R&D, product engineering, and innovation agenda.

With more than half of Esko's global R&D strength now based in India, the ambition is shifting from how much work India can deliver to what India can own. Vivek explains how Esko is building deeper capabilities across cloud engineering, AI, platform architecture, and product engineering while combining them with the specialized domain expertise required in the packaging industry.

What you'll hear:

• Why Esko is evolving its India GCC from a capacity and execution center to a capability and ownership center
• How Esko is building a connected, multi-tenant, AI-enabled packaging cloud spanning the source-to-shelf journey
• The role of AI, knowledge graphs, APIs, digital threads, and agentic workflows in the future of packaging technology
• How Esko is strengthening India's capabilities in cloud-native engineering, AI, machine learning, DevOps, cybersecurity, platform architecture, and product engineering
• Why bringing engineering, customer support, and cloud operations together creates a stronger customer learning loop and helps turn customer feedback into product intelligence
• Why the next measure of GCC success will be business outcomes and global ownership, rather than headcount or the amount of work transferred to India

Looking ahead, Vivek describes an India GCC taking end-to-end ownership across product architecture, engineering, operations, and customer outcomes, with the ability to accelerate strategic product launches, build platform capabilities for global customers, and create IP and expertise that strengthens Esko's competitive advantage.

In this episode of HFS Unfiltered, David Cushman speaks with EY's Dan Diasio and Thiru Vengadam about what it takes to move from AI experimentation to enterprise-scale agentic operations. Drawing on EY’s recognition as a Horizon 3 Market Leader in the HFS Horizons Agentic Services 2026 report, they discussed why the biggest barriers to AI adoption are no longer technology, but business transformation, governance, operating models, and workforce readiness.

The conversation explores how organizations can move beyond proof-of-concept projects by embedding AI into core business operations, building trusted agentic systems with strong governance, and adopting outcome-based partnerships. They also discuss the evolution of Services-as-Software™, where AI-enabled services are creating new business value by combining software, human expertise, and continuous innovation.

Key takeaways

• AI success is a business transformation challenge, not just a technology one.
• Scaling AI requires rethinking operating models, processes, data, governance, and talent.
• Agentic AI must be built on trust. Governance, security, auditability, and human oversight are essential for deploying enterprise-scale AI systems.
• Partnerships are evolving. Organizations need deeper co-development and outcome-based collaborations rather than traditional vendor relationships.
• Services-as-Software™ is reshaping enterprise services. AI enables organizations to combine software with human expertise to deliver new, higher-value outcomes.
• The future belongs to enterprises that embed AI into operations, not just experiments.
• Sustainable value comes from integrating AI into the way work is designed and delivered.

In this episode of HFS Unfiltered, Saurabh Gupta, President of HFS Research, joins Vinod Kumar, President and CEO of Akkodis North America, to explore why AI must move beyond cost savings to deliver real business transformation.

They discuss the convergence of IT, OT, and business transformation, why enterprise AI struggles to move from pilots to production, and how engineering-led AI can accelerate time to market, improve product outcomes, and create competitive advantage.

What you’ll hear:

• Why enterprise AI struggles to move from POCs to production
• How contextual and undocumented data can hold AI back
• Why forward-deployed engineers are becoming increasingly important
• How AI can transform engineering, product validation, and speed to market
• Why trust, safety, traceability, and human oversight remain critical
• How leaders can shift the AI conversation from cost savings to competitive advantage

In this episode of HFS GCC Advantage, Rajeev Gangal, Senior Vice President, R&D Engineering at Mastercard, shares how the company is using its India center in Pune as a strategic innovation hub for AI, product development, and emerging technologies. The conversation explores how Mastercard measures AI impact through tangible business outcomes, accelerates product development across the full lifecycle, and builds trust in next-generation payment experiences. Rajeev also discusses the role of external collaboration, startup partnerships, and GCC culture in driving innovation at scale.

What you’ll hear

• How Mastercard’s Pune hub supports global R&D and innovation
• Why AI is being applied across the full product development lifecycle, not just software delivery
• How Mastercard measures AI value through business outcomes, customer satisfaction, and speed to production
• Why fraud detection, dispute resolution, and digital identity are important AI use cases
• How Mastercard balances innovation with trust, reliability, and security
• Why dedicated R&D enables “zero to one” innovation
• How the company works with startups, universities, and external partners
• What GCC leaders can learn about building a culture of innovation beyond delivery
• How agentic commerce and secure digital experiences may shape the next phase of payments

Key takeaways

• AI creates the most value when tied to measurable business outcomes
• GCCs can drive strategic innovation, not just operational execution
• Trust, security, and speed must advance together in financial services
• Dedicated R&D teams help move ideas from concept to production faster
• External partnerships can strengthen internal innovation engines
• The future of payments will be shaped by agentic commerce and digital identity

In this episode of HFS Unfiltered, HFS’ Ashish Chaturvedi and Hridika Biswas are joined by Nagaraj Sastry, SVP and Global Head of Data and AI for Digital Business Services at HCLTech, to explore a critical enterprise AI paradox: organizations are gaining faster insights and efficiencies from data and AI, but only a small percentage are translating those investments into new revenue and meaningful transformation.

The conversation explores why infrastructure-led modernization alone isn’t enough and how strong data governance, domain ontologies, contextualized intelligence, agentic AI, and operating model redesign can help enterprises move from AI experimentation to measurable business value. Nagaraj also shares how HCLTech is approaching this shift through its data and AI capabilities and industry-specific solutions.

What you’ll hear:

• Why faster insights aren’t necessarily translating into new revenue
• How domain ontologies and trusted data foundations can unlock AI value
• Why process and operating model redesign are essential for scaling agentic AI
• What separates enterprises monetizing AI from those still treating it primarily as infrastructure

In this episode of HFS GCC Advantage, Ramkumar Narayanan, EVP, Enterprise AI and Data Platforms, and Head of FIS India and the Philippines, shares how FIS is turning its GCC into a strategic engine for AI, platform innovation, and business growth. The conversation explores how a mature GCC can move beyond execution to ownership, create enterprise value, and help shape the future of work in a regulated financial services environment. Ramkumar also explains why AI transformation and workforce resilience must advance together, and how India and the Philippines centers are becoming central to FIS’s long-term growth strategy.

What you’ll hear:

• How FIS serves the banking, payments, and capital markets ecosystem
• Why India and the Philippines are strategic GCC centers for FIS
• How the organization is shifting from application-centric work to platform-centric AI
• Why reusable AI foundations help reduce rework and duplication
• How governance is being embedded into code for scale and compliance
• Why AI investments must begin with real business problems
• How GCCs can move from execution to enterprise outcome ownership
• Why workforce resilience must advance alongside AI transformation
• How GCCs can unlock workflow intelligence to support AI redesign
• What leaders should do to stay aligned with the shifting company strategy

Key takeaways:

• GCCs create more value when they own outcomes, not just tasks
• Platform-first AI is more scalable than one-off experiments
• Governance built into code helps regulated enterprises move faster with confidence
• AI transformation and workforce transformation must happen together
• GCCs hold unique workflow knowledge that can shape enterprise AI
• Mature GCCs should align closely with the CEO and company priorities

Join Achyuta Ghosh and Dr. Rajesh Puneyani, Vice President and Site Leader at Kenvue Solutions, for a sharp conversation on how GCCs are evolving from delivery hubs into connected enterprise engines. Rajesh shares how Kenvue built its India center with business impact at the core, why data became the first major capability, and how the team is using technology to improve on-shelf availability, recover lost sales, and support growth across the enterprise.

What you'll hear:

• Why Kenvue GCC was designed from day one as a digital-first, data-driven, business-tech partner rather than a cost center.
• How the India center helps connect consumers, brands, supply chain, data, and technology to drive real enterprise outcomes.

Key takeaways:

• Why is data the foundation for creating connected enterprise outcomes, especially in a consumer healthcare business with a deep product legacy.
• How Kenvue used data and technology to build an on-shelf availability solution that helps recover lost sales and improve market performance.
• Why the next phase of GCC value will come from leadership upskilling in data and AI, not just from adopting tools.
• How business problems and technology solutions need to be married closely to avoid building in the wrong direction.
• Why forward-deployed engineers and business proximity will matter more as GCCs become more outcome-led.
• What separates operational hubs from true growth engines: proactiveness, solution thinking, and the ability to identify problems before headquarters does.
• Why the most successful GCCs will combine operational excellence with the confidence to shape the enterprise roadmap.

In this episode of HFS Unfiltered, Rohan Kulkarni, Executive Research Leader for Healthcare and Life Sciences at HFS Research, joins Titus Leo, SVP of Sagility Provider Solutions, to discuss the HFS Horizons HCP Provider Services 2026 study and explore how healthcare providers can respond to growing financial pressure, rising costs, and changing reimbursement models.

What you’ll hear:

• Why traditional healthcare operating and reimbursement models are becoming unsustainable
• Three bold ideas: direct-to-employer capitation, smarter self-pay strategies, and AI-enabled proactive care
• Why healthcare services are shifting from FTE-based to outcome-based models
• How clinical RCM, agentic AI, and patient engagement can improve financial and operational performance
• How Sagility is advancing these capabilities through Synchrony, AI/GenAI, and Birch AI

Key takeaways:

• Providers need new revenue and care models to build resilience amid continued margin pressure.
• AI can move healthcare from reactive treatment toward proactive disease prevention and management.
• Outcome-based partnerships will increasingly require service providers to deliver measurable business and clinical impact.
• The convergence of services-as-software, RCM, and agentic AI is creating new opportunities to transform healthcare operations.

Learn more about the associated reports here:

In this episode of HFS GCC Advantage, we speak with Saraswathi Ramachandra, MD & Country Head at Lightcast India, about how GCCs are evolving from delivery centers into hubs for product, engineering, and business outcomes. She shares how Lightcast turns labor market data into actionable intelligence and how India is playing a central role in building global capabilities.

What you’ll hear:

• How Lightcast uses labor market intelligence to understand skills and workforce trends
• Why the India GCC is moving from delivery to deeper engineering and product ownership
• How data, AI, and taxonomy power Lightcast’s platform and insights
• What it takes for GCCs to move closer to revenue, customers, and market outcomes

Key takeaways:

• Skills intelligence is becoming essential for enterprises, academia, and governments
• GCCs create more value when they own outcomes, not just tasks
• India can be a strategic hub for AI, data, and product innovation
• The future of GCCs is defined by business impact, customer success, and measurable results

In this episode of HFS Unfiltered Stories, Saurabh Gupta, President of HFS Research, speaks with Manohar Atreya, Chief Operating Officer of iOPEX, about turning Services-as-Software™ from concept into reality and why outcome-led, AI-driven delivery requires moving beyond traditional FTE and effort-based models.

Manohar shares how iOPEX embeds intelligence into business workflows across revenue and service operations, with real-world examples spanning advertising, cybersecurity, telecom, and field services. They also explore why enterprises remain stuck in AI pilot purgatory, how to address data, process, technology, and talent debt, and why successful AI transformation starts with the right business case rather than large-scale modernization.

The conversation closes on the growing opportunity for outcome-based models, AI orchestration, and services delivered as intellectual property, and why Services-as-Software represents a new model for enterprises and providers to learn to buy and sell.

Most GCCs still focus on scale and cost. Evernorth Health Services is doing something different.  In this episode, Prashanthi Bodugam, Head of Evernorth Health Services India, shares how her team has transformed a fast-growing GCC from a traditional shared services model into an AI-first strategic hub in under two years. It’s a practical look at how healthcare GCCs can move past cost arbitrage and start driving real enterprise value. Prashanthi dives into what it takes to reimagine workforce skills, build responsible governance, and embed AI into core outcomes such as claim processing and patient care. Her point is direct: AI works best when it amplifies human expertise rather than replaces it, and the next frontier for GCCs is deep integration of AI into enterprise workflows.

With over 20 years of leading GCCs and shaping Cigna’s India operations, Prashanthi offers a blueprint for quickly scaling innovation without sacrificing trust or compliance. If you’re a healthcare leader, CTO, or CFO trying to unlock real AI value in a regulated industry, this one is worth your time.

What you’ll hear:

• Why healthcare GCCs are moving beyond cost savings
• How Evernorth is transforming in under two years
• Why AI literacy and responsible governance matter
• Real AI use cases in claims processing and patient care
• How to build an AI-first culture without losing human oversight

Key takeaways:

• GCCs can create strategic value beyond execution and scale
• AI works best when paired with human oversight and governance
• Practical use cases like claims automation deliver real impact
• Workforce upskilling is essential for AI adoption
• Healthcare leaders must balance innovation, Trust, and compliance

In this episode of HFS Unfiltered, Hansa Iyengar, Practice Leader at HFS Research, speaks with David McQueen, EY's Global SAP Consulting Managing Partner & Global Consulting Executive Committee Member, about what separates a technically successful SAP S/4HANA migration from a transformation that delivers real business value. The discussion follows EY's recognition in Horizon 3 of the HFS SAP S/4HANA Transformation Services Horizons.

David explains why successful ERP transformation depends on three fundamentals: clean, well-governed data, deep process expertise, and strong, business-led change management. While AI is accelerating ERP programs, it amplifies the importance of these foundations rather than replacing them.

The conversation also explores outcome-based transformation, including EY’s "phase zero" approach and the Transformation Realized platform, which helps define value up front and align commercial models with measurable business outcomes. David argues that future success depends on shared accountability between clients and systems integrators.

They conclude by discussing the need for stronger business ownership, cross-functional collaboration, and better governance throughout transformation programs. David’s key takeaway is clear: SAP transformations succeed when they’re treated as business initiatives supported by technology, not technology projects alone.

In this episode of HFS Unfiltered, Achyuta Ghosh of HFS Research speaks with Ashok Chawla, Co-Chief Delivery Officer at RSI (formerly R Systems), following RSI’s recognition as a Horizon 2 player in the HFS GCC Services Horizons report. They explore how mid-market GCCs are being built AI-native from the start and shifting from operational metrics and cost efficiency to business outcomes, product innovation, and co-creation.

What you’ll hear:

• How RSI takes an AI-first approach to building and transforming GCCs
• How GCC’s co-pilot and EXIQO AI Studio support AI-native transformation and workforce reskilling
• How a healthcare GCC achieved 30–40% higher productivity than its headquarters within six months
• How RSI’s C-Osmosis model helps existing GCCs transform teams and embed AI into products

Key takeaways:

• GCC success is increasingly measured by business outcomes, not operational metrics
• AI-native talent and operating models are becoming essential
• GCCs are evolving from cost centers into hubs for product innovation and growth
• Co-creation and agentic product transformation will be key differentiators

In this episode of HFS GCC Advantage, Sunil Gopinath, CEO of Albertsons Companies India, shares how the India GCC has evolved into a strategic engine for enterprise AI, product ownership, and business transformation. He explores the shift from delivery to end-to-end outcome ownership and how AI is helping Albertsons improve decisions, operations, and customer experiences at scale.

What you’ll hear

• How Albertsons India evolved from support to end-to-end ownership
• Why AI must improve real business decisions to create value
• Why a platform approach, governance, and data quality are critical for scaling AI
• How AI supports predictive operations, root-cause analysis, and AIOps
• Why adoption is the true measure of AI maturity

Key takeaways

• GCCs become strategic when they own business outcomes
• Enterprise AI requires strong governance, data, and scalable platforms
• AI should augment decisions, not simply automate processes
• Adoption and measurable impact matter more than launching pilots
• The future of GCCs lies in deeper ownership and business alignment

This episode explores what it really takes to move AI beyond pilots and deliver enterprise-wide impact. It highlights why successful AI adoption depends on more than technology, emphasizing the critical roles of leadership, culture, collaboration, and operational readiness. The conversation also examines the mindset shift organizations need to scale AI with confidence, break down silos, and transform experimentation into measurable business value.

Featuring Achyuta Ghosh, Executive Research Leader at HFS Research, and Sameer Shaikh, Senior Director, Technology & FSS at XPO, this discussion brings together industry research and real-world enterprise experience to explore the challenges, opportunities, and practical strategies for scaling AI across the enterprise.

What you'll hear

• Why a learning mindset is essential for scaling AI
• How breaking down silos improves adoption across large organizations
• Why data readiness and process redesign are critical to success
• The role of leadership, governance, and psychological safety in AI adoption
• How to move AI from isolated pilots to enterprise impact
• Why AI should become a habit, not just a project

Key takeaways

• Culture is a major driver of AI success at scale.
• Collaboration and shared ownership help AI spread across the enterprise.
• Data readiness and process redesign are key foundations for impact.
• Leadership and psychological safety support experimentation and adoption.
• AI delivers the most value when it is embedded into everyday business operations.

In this episode of HFS GCC Advantage, we speak with Shalini Sankarshana, Managing Director, Planview, Inc., about how Planview’s India GCC has evolved from a capability center into a strategic engine for product ownership, engineering, business accountability, and market growth. Shalini shares how the team built end-to-end ownership across major products, expanded into AI-led innovation with the Anvi platform, and is now helping drive India as both a talent base and a revenue opportunity.

What you’ll hear

• How Planview built its India GCC with a clear strategy from the start
• The shift from support work to product engineering ownership
• How India now runs 8 of 16 products end-to-end
• Why the team focused on global capability building and operational optimization
• How Planview is using AI and the ANVI platform to reshape product and platform strategy
• What it takes to move from a cost center to a revenue-generating business unit
• How India is becoming both a talent hub and a market growth engine

Key takeaways

• India GCCs are evolving from support centers into strategic business hubs.
• Early ownership of business problems builds stronger trust and accountability.
• Product engineering and operations can be redesigned for global, self-sufficient teams.
• AI is becoming central to platform strategy, governance, and decision-making.
• India is increasingly important not just as a talent location, but as a market and growth engine.
• The future of GCCs is deeper ownership, stronger customer orientation, and clearer business outcomes.

In this episode of HFS Unfiltered, Saurabh Gupta, President of HFS Research, is joined by Anuj Krishna, Cofounder and President - Technology & Growth of MathCo, to discuss one of the least understood reasons enterprise AI stalls: the absence of context.

The pattern is everywhere. Enterprises have sky-high AI ambitions, yet pilots multiply and almost none reach production, what Saurabh calls “death by a thousand POCs.” In research HFS and MathCo ran together, roughly two-thirds of enterprises admitted they don't know where their knowledge lives; it's trapped in people's heads, undocumented processes, and scattered data. Anuj's argument: organizations obsess over models when the real advantage lies in context, who they are, how they work, and the knowledge behind their decisions.

The conversation goes deep on what context actually is, why it can't be static, and who should own it, including the shift toward a federated model with “context stewards” by function. Anuj also lays out how MathCo differs from the platform owners and SIs racing to be “context kings”: rent the tech ecosystem, but own the intelligence, because you can't own your intelligence unless you own your knowledge, and an organization's context is its personality. Saurabh closes with a sharp thesis: models and agents will become a utility, and neither will differentiate you, but context is your identity, and owning it is the only sustainable advantage going forward.

Global in-house centers and Global Business Services are no longer just about efficiency and scale. In this conversation, Arvind Shankar from Reckitt shares how GCCs are being reshaped by human-centered transformation, enterprise orchestration, and AI-driven operating models. From talent redesign to governance and tacit knowledge, this episode explores what it takes to build future-ready organizations that create real business outcomes.

What you'll hear

• How GCCs and GBS are evolving from process efficiency to enterprise orchestration
• Why human-centric, outcome-based transformation models matter
• What the future of talent looks like in the GenAI era
• How organizations can move from AI pilots to enterprise-wide orchestration
• The role of trust, governance, and organizational context in AI adoption
• Practical examples of AI in regulatory workflows and marketing
• Why operating models need to shift from SLAs to value creation

Key takeaways

• The future of GCCs is less about cost and more about enterprise outcomes.
• Human-centered transformation creates stronger alignment across business, talent, and technology.
• AI success depends on orchestration, governance, and contextual knowledge—not just tools.
• Organizations need AI fluency, but also new leadership and operating capabilities.
• Tacit knowledge and organizational context are becoming key competitive advantages.

Join us as Mani Ganesan, SVP and Head of APAC Engineering at Amadeus Labs India, shares how the India Center evolved from a cost center to a strategic hub driving product innovation, revenue, and global leadership in travel technology. Discovers how Amadeus leverages AI, builds global roles, and creates a unique employer brand in India to support the future of travel tech.

What you'll hear:

• How Amadeus India evolved from a cost-focused operation into a global excellence hub
• How the team uses thought leadership, campus engagement, and brand building to attract top engineering talent
• Why AI fluency is becoming central to the future of travel technology and engineering in India
• How global roles are being built from India to support bi-directional leadership
• What it takes to manage complex, high-volume travel platforms processing over 100,000 transactions per second
• Why the Indian travel ecosystem creates unique opportunities for localized innovation and scale

Key takeaways:

• Why moving beyond cost-center thinking is essential for GCCs that want to create real business impact
• How employer brand and campus presence help build a stronger talent pipeline in competitive markets
• Why AI fluency is not just a technical skill, but a strategic capability for future-ready engineering teams
• How GCCs can create global leadership roles from India instead of only supporting headquarters
• Why a deep understanding of local market behavior can unlock better product design and innovation
• What separates a strong delivery center from a true global product and revenue engine
• Why the future of GCCs depends on combining operational excellence with strategic ownership

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.

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.

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.

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.

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 ends

Enterprise 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 hear

• The reality of AI hype vs fear on the ground
• Why modernization feels like a never-ending cycle
• The disconnect between reported success and real outcomes
• Why “bolt-on” approaches fail

Watch 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 platforms

Modernization 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 hear

• The real role of AI in modernization
• Why most enterprises get stuck in pilot mode
• A real-world example of platform-led transformation
• Why data becomes the foundation for AI

Watch 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 hear

• Why modernization must become continuous
• How AI connects systems into a “thread of gold.”
• What real business value from AI looks like
• Practical advice for CIOs to get started

Watch the full series to see how enterprises are rethinking modernization for the AI era, and what it takes to make it work in practice.

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.

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?

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.

HFS Executive Research Leader David Cushman learns how Agentic Tech market leader EMA is going further in productizing agentic work, delivering hard ROI, and building trust in regulated industries.

Key point discussed:

• The importance of redefining what work looks like, why change management is key, and the importance of understanding both business needs and processes, to deliver ROI with AI.

In this episode, HFS Research’s Dana Daher is joined by Genpact’s Ajay Vasal to unpack insights from a new study of over 500 enterprise leaders on what it really takes to scale agentic AI.

While most organizations believe the technology is ready, very few are prepared to let AI act autonomously. The conversation explores why this is not a technology challenge, but an operating model shift that requires rethinking processes, governance, and decision-making at a fundamental level.

Drawing from real-world experience, Ajay shares how enterprises can move beyond pilots and unlock value by redesigning workflows for AI, establishing accountability, and shifting how success is measured. This is a practical discussion on what separates AI ambition from execution.

What you’ll learn

• Why scaling agentic AI is an operating model challenge, not a technology one
• The gap between AI ambition and enterprise readiness
• How to redesign processes for autonomous execution
• What governance and accountability look like in an AI-driven environment
• Why productivity alone is not the right way to measure AI success
• How leading enterprises are moving from pilots to real business impact

Key takeaways

• Most enterprises trust AI to recommend, but not to act
• AI cannot be layered onto processes designed for humans
• Process redesign is critical to unlocking AI value
• Governance and decision ownership must be clearly defined
• Measuring AI through productivity alone limits its true potential
• Organizations that treat AI as a business transformation will scale faster

HFS Research selected OrbitShift as a Hot Tech for its ability to turn fragmented market signals into structured opportunity shaping and pipeline execution through full-stack agentic orchestration.

In this videocast, HFS Executive Research Leader David Cushman sits down with OrbitShift co-founder and CEO Saurabh Mishra to unpack what that really means in practice. Together, they explore how sales teams are navigating an increasingly complex landscape filled with dashboards, signals, and AI tools, yet still struggle to prioritize the right opportunities at the right time.

The conversation looks at how OrbitShift approaches this challenge differently, combining contextual intelligence, real-time data, and agent-driven workflows to support deal shaping and pipeline development. Saurabh also shares where automation works best, where human judgment remains critical, and how this balance is evolving as agent capabilities mature.

From pipeline impact and user experience to the future of agent-to-agent interactions, this discussion offers a grounded view of how sales models are shifting and what it takes to turn signals into meaningful outcomes.

Key points discussed:

• What kind of data makes the biggest difference to sales conversions?
• Where should agentic AI be deployed and where should humans remain at the helm, and how should we prepare for the rise of agent-to-agent sales?

iOPEX CRO Dharmesh Mistry and HFS Executive Research Leader David Cushman discuss how iOPEX applies domain expertise and outcome-based pricing to deliver agentic services in the enterprise.

Key points discussed:

• Dive deeper into iOPEX’s impact in the first-ever HFS Agentic Services Horizons report.
• How are they combining deep domain and process expertise with gain-share commercial approaches to move the needle for a significant client?

What happens when services are no longer delivered through people alone, but through platforms, software, and AI working together?

In this Fireside Chat, Phil Fersht speaks with Jo Debecker, President and CEO at Akkodis, on how the company is shifting from a traditional staffing-led model to outcome-driven digital engineering.

With engineering becoming increasingly digital, Akkodis is combining deep domain expertise with platforms, IP, and AI to accelerate innovation for clients. From building simulation environments for industries like aerospace to enabling faster product development cycles, the focus is on delivering measurable outcomes rather than just effort.

The conversation explores what it really takes to move away from headcount-based services, how sales and delivery models must evolve, and why AI should be seen as an enabler of human potential rather than a replacement.

It also highlights a critical shift ahead. Less experimentation, more focused implementation. Less hype, more real impact.

Cognizant Chief AI Officer Babak Hodjat - Head of the firm’s AI lab in San Francisco, tackles the realities of scaling agentic AI across the enterprise, with HFS Executive Research Leader David Cushman.

Key points discussed include:

• Where multi-agent systems break first - and what that means for the state of progress in agentic AI.
• How an agent OS - a standardized layer for governance, orchestration, observability, data trust, and workforce integration, helps enterprises handle the complexity ceiling they will inevitably hit when scaling the use of agentic AI.
• And what’s the impact of the newly emerged OpenClaw and its promise of end-to-end workflows?

In the latest episode of Unfiltered Stories, Sam Duncan, Practice Leader at HFS, sat down with Paul Brody, Former Global Blockchain Leader at EY, and Clare Adelgren, Global Blockchain Leader at EY, to discuss the findings of the latest HFS Enterprise Blockchain Services Horizon. They concluded that enterprise blockchain is very much alive, but it's become all the right kinds of boring.

Key discussed points include:

• Serious players never stopped investing
• The core drivers of enterprise blockchain today (stablecoins, tokenization)
• How engagements can move to production
• What differentiates leaders in the market

If you think enterprise blockchain is dead, think again.

Everyone wants to be AI-first. But no one wants to fund it. In this HFS Unfiltered Stories conversation, Saurabh Gupta, President at HFS Research, sits down with Kailash Attal, Chief Solutions Officer at UST, to tackle one of the toughest questions facing enterprises today: How do you fund AI when budgets are tight, and legacy costs are high?

With CFO scrutiny increasing and capital discipline at an all-time high, enterprises can’t simply “wait for the next budget cycle.” Instead, a new operating model is emerging, a self-funded transformation, where savings generated from optimization are reinvested directly into AI and innovation.

They together explored:

• Why 8 out of 10 enterprises say they cannot wait to transform
• How to combine “run” and “transform” into one operating model
• Why AI is blurring the lines between IT and business
• How services-as-software becomes realistic through structured self-funding
• What must change culturally and operationally to make this work

This isn’t about cost-cutting. It’s about creating a flywheel of savings, reinvestment, and growth, and if your organization is struggling with the how of AI, this conversation is for you.

In this HFS Research videocast with Mindsprint, Ashish Chaturvedi speaks with Rohit Sharma and Unnikrishnan Sasikumar on how supply chains are moving from visibility to intelligence amid disruption—shifting from AI pilots to outcome-led transformation (working capital, margin, customer experience). They explore what’s driving demand today including real-time planning, control towers, supplier collaboration, predictive analytics and what’s next: agentic AI for exception handling and the path to autonomous supply chains, grounded in trustworthy data foundations and an ecosystem approach across SAP/Microsoft cores plus specialist startups.

Key discussion points include:

1. Enterprise demand today is still centered on “visibility + decision support.” Most current programs focus on real-time planning, control towers, supplier collaboration, and AI-driven dashboards/analytics to enable faster decisions during disruption.
2. Clear shift from tactical work to integrated, tech-enabled operations. Buyers are moving away from manual Excel forecasting and siloed portals toward integrated solutions that support automated exception handling (including agentic AI), plus broader ecosystem collaboration and traceability.
3. A widening “spend today vs build tomorrow” gap is shaping strategy. Enterprises are still investing heavily in analytics modernization, cloud, and data foundations, while major tech vendors are pushing hard on generative AI and agentic architectures—creating a sequencing challenge.
4. Trustworthy data is the gating factor for autonomous supply chains. The conversation emphasizes that without strong data foundations (freshness, accuracy, governance, and resolving conflicting data sources), autonomy can create bad decisions (e.g., stock-out risk when systems think safety stock exists).
5. Organizational capabilities matter as much as technology. Beyond platforms and tools, capability building and guardrails (e.g., CoE / governance frameworks) are positioned as essential to unlock value from data and AI.
6. The partner stack is hybrid: ERP core plus startup innovation. SAP and Microsoft are described as dominant “core” stacks, while many enterprises augment them with specialist startups/scale-ups for niche planning, visibility, risk, and sustainability, requiring an ecosystem approach.
7. Progress is real, but not linear. Enterprises are still getting foundations right, even as the tech investment trajectory points clearly toward more autonomous, AI-driven supply chain operations.

AI-first is table stakes; instead, outcomes-first delivery in collaboration with a partner ecosystem unlocks growth, access, and resilience.

Key discussion points include:

• AI-first is no longer differentiating, but outcomes are. Most providers claim AI-first, but the real shift is to outcomes-first delivery tied to better health, better experience, lower cost, and equity.
• The old delivery playbook won’t survive the revenue headwind and patent cliff era. Life science enterprises need a new operating model, Services-as-Software, to rewire discovery-to-commercial and drive measurable impact.
• Winning suppliers become growth partners, not just capacity providers. The next wave is precision medicine, real-world evidence, global resilient supply chains, and continuous patient engagement; vendors that bring IP/platforms and ecosystem innovation move from Horizon 2 toward Horizon 3.