There’s a widening gap between how organizations believe they are performing and what customers and employees actually experience.
While executives have strong intentions and meaningful technology investments underway to improve the experiences they deliver, they often find that friction persists and small breakdowns compound across customer and employee journeys.
Across industries, these leaders are converging on the same hope: that agentic AI can effectively close the gaps. But most organizations are not yet ready to deliver on it. They are piloting, bolting capabilities onto legacy journeys and discovering in real time that their biggest obstacles have little to do with the technology itself.
From Promise to Practice: The Realities of Scaling Agentic Experiences synthesizes 21 in-depth interviews with C-suite leaders across nine industries and multiple countries. It captures what leaders are learning as they move toward agentic experiences capable of delivering customer outcomes at scale. The report also synthesizes the practical constraints and design requirements that determine whether agentic AI becomes a front-end novelty — or a true end-to-end experience advantage.
The finding is consistent across every industry we studied: technology is not the differentiator. The organizations pulling ahead are the ones that started with the experience — what customers and employees should feel, trust and return to — and built their AI strategy around it. Industry-specific insights from industries including healthcare, financial services, and retail and consumer underscore that while contexts differ, the leadership imperative is the same.
Key takeaways
The data problem isn’t one problem.
Ask executives what’s blocking their agentic AI ambitions and “data” will be part of the answer. Yet the data problem is not a single challenge. It involves distinct problems that require different solutions. These challenges include data fragmentation, accessibility to AI systems, governance constraints, and data that’s unstructured or unrecorded.
AI is only as good as the people working alongside it.
Every organization we spoke with has a policy for human involvement in agentic AI processes. Healthcare cites regulatory guidance. Banks cite risk thresholds. Most others cite trust and accountability. The positions are clear and often carefully considered. However, what almost none has done is design what it means for employees to work alongside AI — and consider how that directly shapes the customer experience.
Your brand is no longer a guideline. It’s code.
If an AI agent writes to a dissatisfied customer, responds inappropriately to a worried patient or declines a request, what does your brand sound like in that moment? Leaders are learning they need to define their brand with a new level of precision, and enforce operational parameters through machine-executable code that governs AI behavior in ways a brand guideline cannot.
A pivot separates leaders from laggards.
Across 21 conversations and nine industries, the organizations delivering the most measurable impact from agentic AI share almost nothing in terms of sectoral priorities, technology stacks, geography or budget. What they share is a single pivot. At some point in their AI journey, each stopped asking what technology can do, and started asking what the experience should be.
The 9Es
The 9 Es is our practical experience outcome lens for evaluating whether an agentic AI experience is truly delivering on its promise — across nine dimensions organized into three questions:
- Is the experience optimized? Is it efficient, effective and economically viable?
- Is it humanized? Are experiences designed to be empathic, ethical and empowering?
- Is it truly holistic? Are organizations evolving, prioritizing educational design and working toward end-to-end experiences?
Organizations delivering measurable, lasting results are working across all of the 9Es. Leading CXOs are proving performance-optimized outcomes, designing for trusted, human-centered experiences, and orchestrating end-to-end delivery at scale.
Read more about AI and experience design at Kyndryl
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