HFS PODCASTS

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.

In this episode of Unfiltered Stories, HFS Research President Saurabh Gupta sits down with Eric Piscini, CEO of Hashgraph, to explore the real intersection of AI and blockchain and why trust is becoming the defining challenge for both.

While AI is rapidly reshaping enterprise workflows, one question continues to surface. Can we trust it? This conversation dives into how distributed ledger technology is quietly emerging as the trust layer for AI, enabling transparency, control, and accountability in a world driven by autonomous systems.

From stablecoins and tokenization to AI-driven payments and decentralized governance, Eric shares how blockchain is moving beyond hype into real enterprise adoption. If you are thinking about the future of AI at scale, this conversation connects the dots between two of the most important technologies shaping it.

What you’ll learn

• Why trust is the biggest barrier to enterprise AI adoption
• How blockchain can act as a control and audit layer for AI systems
• The real differences between stablecoins, tokenized cash, and CBDCs
• How AI and blockchain are converging to enable new business models
• What asset tokenization means for enterprises and individuals
• How AI-driven payments and autonomous agents will reshape transactions

Key takeaways

• AI and blockchain are complementary technologies, not competing ones
• Blockchain enables transparency and accountability for AI decisions
• Enterprise adoption of blockchain is accelerating due to regulatory clarity
• Tokenization has the potential to unlock new forms of value and access
• AI-driven agents will require trusted payment and transaction systems
• The future of trust in digital systems will be built into the infrastructure

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.

Learn more about the 2026 HFS Agentic Services Report - covering 35 service providers: https://www.hfsresearch.com/research/hfs-horizons-agentic-technology-2026/

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

Also, read the associated Market Impact Report titled "Autonomy requires trust in AI", here: https://www.hfsresearch.com/research/autonomy-requires-trust-in-ai/

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?

Read the HFS Hot Tech report, titled “HFS Hot Tech: OrbitShift”, here: https://www.hfsresearch.com/research/hfs-hot-tech-orbitshift/

Healthcare is undergoing a serious transition away from hardware-centric systems toward software-defined and physical AI-enabled healthcare environments.

Healthcare is also moving toward a paradigm that is proactive, personalized, and ambient, leveraging intelligent technologies to improve patient care, operational efficiency, and clinical outcomes.

The conversation explores how technologies such as advanced diagnostics, surgical robotics, remote monitoring, and smart medical devices are reshaping healthcare delivery. Gopal also shares practical insights into the challenges the industry faces around regulation, cybersecurity, data interoperability, verification and validation, and operational transformation.

Most importantly, the discussion highlights how healthcare is gradually moving from reactive treatment models toward more proactive, personalized, and patient-centric care by 2030.

This is a valuable conversation for healthcare leaders, technology executives, and anyone interested in the future of healthcare innovation.

Watch this insightful interaction Ramachandran S, HFS Research, had with Gopalratnam VC, Executive Vice President and Global CIO at Philips, on the move toward software-defined healthcare.

Key Takeaways

• Software is becoming the key differentiator in modern medical devices.
• Intelligent systems and robotics are improving precision and operational efficiency in healthcare.
• Verification, validation, and compliance remain critical in healthcare technology adoption.
• Data fragmentation and lack of interoperability continue to slow innovation across healthcare ecosystems.
• The healthcare industry is moving toward more proactive and preventive care models.
• Personalized healthcare experiences will become increasingly important by 2030.
• Automation can help reduce administrative burdens for clinicians and healthcare staff.
• Future healthcare systems are expected to become more connected, efficient, and patient-focused.

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?

Learn more about the 2026 HFS Agentic Services Report - covering 35 service providers: https://www.hfsresearch.com/research/hfs-horizons-agentic-services-2026/

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.

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