On this page, you’ll find a curated collection of key takeaways, event photos, video highlights, and analyst insights that capture the spirit and substance of this roundtable event. We invite you to dive in and experience the bold, unfiltered thinking that defines HFS Research.

Highlights from this HFS Executive Roundtable

HFS Research, in collaboration with IBM Consulting, convened senior executives for a forward-looking discussion on what must change before AI can propel real enterprise performance. While participants agreed that AI has proven useful across marketing, IT, and customer service, they were clear that technology alone cannot overcome fractured processes, hesitant governance, and outdated decision-making. The discussion centered on rebuilding organizational muscle for change, aligning leadership and investment, and equipping modern talent to move from incremental efficiency to true performance transformation.

What we heard

The roundtable surfaced five powerful insights shaping how enterprises can turn AI potential into measurable impact:

  1. AI is useful but not yet performance-defining:
    Enterprises are deploying AI broadly for efficiency and personalization—but these efforts remain peripheral to revenue growth, profitability, and market share. Generative AI is augmenting operations rather than revolutionizing them.
  2. Change management and process renewal matter more than data debt:
    The biggest obstacle isn’t legacy systems—it’s the absence of strong change management and reengineered workflows. Without disciplined redesign, AI risks amplifying dysfunction rather than resolving it.
  3. Unified decision-making is critical for scale:
    Fragmented ownership and siloed AI programs dilute impact. A single, coherent governance structure and investment line are essential to scale AI responsibly and consistently across the enterprise.
  4. Personalization is advancing but impact is narrow:
    AI-driven personalization is yielding impressive marketing and engagement wins—IBM’s marketing reinvention, for instance, cut creative cycles from six weeks to six seconds—but few enterprises have yet linked these gains to overall performance outcomes.
  5. Talent and institutional capability remain decisive:
    Sustainable performance depends on cultivating consultative, domain-rich, and adaptive talent. Automation that focuses solely on cost-cutting risks eroding the expertise needed for long-term competitiveness.

Scenes from the Roundtable

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Executive Interviews: Perspectives That Push the Conversation Further

We captured three dynamic interviews that continue the roundtable’s bold conversation. 

Scaling AI Beyond the Pilot: IBM’s $3.5B Playbook

Jean-Stephane Payraudeau, Managing Partner at IBM Consulting, shares how IBM scaled AI-led automation to deliver $3.5B in value and why true transformation requires more than technology—it’s about rethinking models, processes, governance, and skills.

AI alone won’t fix broken operations

Aparna Sharma, Senior Partner and Global VP at IBM Consulting, shares how AI drives both growth and efficiency—enhancing customer experiences and innovation while optimizing operations across the value chain. The takeaway: AI can boost revenue and margins at the same time.

AI Without Trade-offs: IBM’s $4.5B Efficiency + Growth Story

Ari Sheinkin, CMO at IBM Consulting, discusses how the company used AI to cut $4.5B in costs while fueling growth—proving efficiency and expansion can go hand in hand. As IBM’s own “client zero,” the team shows how AI delivers speed, quality, and cost benefits across functions and industries.

What’s next?

The conversation about AI as a driver of enterprise performance is just beginning—and the implications are profound. If your organization is confronting the limits of efficiency-led AI or seeking to align leadership, talent, and technology for sustainable growth, we’d love to continue the dialogue. Let’s connect to explore how to evolve from experimentation to enterprise-wide transformation. 

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