Last quarter, a CIO at a mid-market financial services firm told me something that stuck: “I have 14 browser tabs open right now—vendor whitepapers, analyst reports, a McKinsey deck from 2024, three Medium posts about agent architectures. None of them agree on anything, and none of them tell me what to actually do on Monday morning.”
He’s not alone. According to McKinsey’s 2025 State of AI survey, 62% of organizations are experimenting with AI agents—but in any given business function, no more than 10% have actually scaled them. The gap between “we’re exploring agentic AI” and “we’re getting value from agentic AI” has become the defining challenge for enterprise leaders this year.
The Practical Resource Gap
The information problem isn’t a lack of content—it’s a lack of useful content. Vendor guides are biased toward their own platforms. Academic research is fascinating but rarely translates to a Monday morning action plan. And the consulting firms that produce genuinely practical frameworks charge $50,000 or more for the privilege of reading them.
Meanwhile, Gartner predicts that over 40% of agentic AI projects will be canceled by the end of 2027, citing escalating costs, unclear business value, and inadequate risk controls. Their analysts note that most agentic AI propositions today “lack significant value or return on investment, as current models don’t have the maturity and agency to autonomously achieve complex business goals.” When 40% of projects are headed for cancellation, the difference between success and failure often comes down to whether leaders had the right planning tools before they started.
Enterprise leaders need something in between a sales pitch and an academic paper—practical, vendor-neutral resources that help them evaluate, plan, and govern agentic AI with clear eyes. That’s exactly what we built.
Introducing Future of Agentic
Future of Agentic is a free, comprehensive research site designed for enterprise leaders navigating agentic AI. No gating, no lead forms, no vendor spin. It’s the resource we wished existed when we started building Olakai—and the one we kept hearing customers ask for. Here’s what’s inside.
A KPI Library Built for Business Leaders, Not Data Scientists
One of the most common questions we hear is deceptively simple: “How do I know if my AI agent is actually working?” The interactive KPI library provides 18 metrics across agentic, chatbot, and AI application categories—each with definitions, calculation methods, benchmarks, and guidance on when to use them. These aren’t abstract metrics. They’re the specific measurements that separate organizations scaling AI successfully from those stuck in pilot purgatory. Think agent task completion rate, autonomous resolution percentage, and cost per automated decision—KPIs that connect directly to business outcomes your CFO will understand.
ROI Calculators That Go Beyond Napkin Math
Every enterprise leader considering agentic AI needs to answer two financial questions: What will this actually cost, and what happens when agents stop delivering value? The Agent Economics section includes two interactive calculators. The Agent TCO vs. FTE calculator models the real total cost of ownership—infrastructure, maintenance, monitoring, and iteration—against human equivalents over time. The Zombie Agent Cost calculator tackles a problem most vendors don’t want to discuss: the ongoing expense of agents that are deployed but no longer delivering meaningful results. Both tools produce shareable outputs, so you can bring data-backed projections to budget conversations instead of guesswork.
Hundreds of Enterprise Use Cases, Sorted by What Matters
The use case library catalogs hundreds of enterprise applications of agentic AI, each with architecture context and complexity ratings. What makes this different from a typical “top 10 use cases” listicle is the filtering: sort by department, by implementation complexity, or by business function to find the applications that match your organization’s maturity and priorities. Whether you’re a head of customer success exploring automated escalation workflows or a CISO evaluating security operations agents, the library narrows the field to what’s relevant.
Governance Frameworks for the Enterprise, Not the Lab
The Deloitte State of AI 2026 report found that only 21% of organizations have mature AI governance models in place—even as 38% are actively piloting AI agents. That governance gap is a ticking clock. The governance section on Future of Agentic provides risk assessment frameworks, compliance checklists, and decision-making guides built for enterprise reality. These aren’t theoretical policy templates — they complement our own CISO governance checklist and are structured around the actual decisions leaders face: What level of autonomy should this agent have? What happens when it fails? Who’s accountable? How do we audit it?
An AI Readiness Quiz (30 Seconds to Your Roadmap)
Sometimes the most valuable tool is the simplest. The AI readiness assessment takes about 30 seconds, asks targeted questions about your organization’s current AI maturity, and produces a customized roadmap with recommended next steps. It’s not a lead-gen funnel—it runs entirely in the browser and gives you immediate, actionable output. We’ve seen leaders use it to align executive teams on where they actually stand versus where they think they stand, which often turns out to be a more productive conversation than any strategy offsite.
The Enterprise AI Unlocked Podcast
Research and frameworks are essential, but there’s no substitute for hearing how other leaders are navigating these challenges in practice. Enterprise AI Unlocked features in-depth conversations with enterprise leaders and practitioners—from Fortune 500 AI playbooks to the real economics of voice AI deployments. Six episodes are live, with new conversations publishing regularly. Each episode is enriched with chapters and participant context so you can jump directly to the topics that matter most to you.
Who This Is For
We built Future of Agentic for the people making decisions about AI in their organizations: CIOs evaluating agent architectures, CISOs building governance frameworks, CFOs modeling AI agent ROI, and Heads of AI or Data leading implementation. But it’s equally valuable for the product managers, directors, and team leads who need to build informed business cases and present them upward. Everything on the site is free and ungated—because we believe better-informed leaders make better decisions, regardless of whether they ever become Olakai customers.
Where Olakai Fits
Future of Agentic is the research and planning phase—understanding what’s possible, modeling the economics, and building a governance framework before you deploy. Olakai is the execution and measurement phase—tracking ROI, governing risk, controlling costs, and securing AI usage once agents are live in production. The two are complementary by design: plan with Future of Agentic, then measure and govern with Olakai.
Start Exploring
If your team is navigating agentic AI decisions right now—or preparing to—explore Future of Agentic. Start with the KPI library if you need measurement frameworks, the use case library if you’re evaluating where agents fit, or the readiness quiz if you want a quick pulse on organizational maturity. And when you’re ready to move from planning to production, schedule a demo of Olakai to see how measurement and governance work in practice.