You're Not Behind Yet. But You Will Be If You Don't Start Learning This Now.
- Philip Lamb
- May 6
- 7 min read
Updated: May 23
Something that might surprise you, coming from someone who talks about agentic AI every week: most companies have not deployed it yet.
Not because they lack the budget. Not because they have failed to understand the technology. Most companies have not deployed agentic AI yet because the build-out is harder than the headlines suggest, and the organizational ownership problem turns out to be harder to solve than the technical problem. That is a solvable problem. It is not a reason to wait.
The good news: you are not behind. The early mover advantage is still available. The window is still open.
The warning is that statement has a shelf life, and the clock is running.
McKinsey's 2024 State of AI report found that only 23 percent of companies have deployed AI capabilities across more than one business function. Gartner projects that by 2028, 33 percent of enterprise software applications will include agentic AI, up from less than 1 percent in 2024. Those two numbers describe the same window. The space between where adoption is today and where it is heading in the next four years is where the next competitive separation gets built. The companies that move in this window will look back at 2026 the way early CRM adopters looked back at 2001.
Where Do Most Pittsburgh Businesses Actually Stand on Agentic AI Right Now?
Most Pittsburgh and Western Pennsylvania business leaders fall into one of three groups when it comes to agentic AI adoption, and the group they are in right now determines how hard the catch-up becomes later.
Group 1 has not yet prioritized AI. They are running the same workflows they were running five years ago. AI is something they read about, something they plan to address, but it has not become a strategic priority. This is not unusual. Most of the business press focuses on enterprise-level deployments at companies with massive technology organizations and dedicated AI teams. For a mid-market manufacturer in Allegheny County or a professional services firm in Pittsburgh's central business district, the gap between reading about agentic AI and deploying it is not obvious.
Group 2 is experimenting. Someone on the team has ChatGPT running in a browser tab. The company may have rolled out Microsoft 365 Copilot. They are testing and occasionally impressed. But nothing structural has changed. The ROI conversation has not happened. The workflow audit has not happened. The question of what data is available and whether it is in usable condition has not been seriously asked.
Group 3 is building. They have identified specific workflows where agent deployment generates measurable return. Lead qualification. Client reporting. Scheduling coordination. Proposal generation. Data reconciliation across systems. They are connecting tools and they are learning with every iteration. Every week in Group 3 generates information that makes the next deployment faster and more targeted.
Group 3 is still a small minority. In regional markets like Pittsburgh and Western Pennsylvania, the number of companies with agentic AI in active deployment is small enough that companies moving now are still capturing genuine first-mover advantage. That will not remain true indefinitely. Technology adoption in business markets does not move in a straight line. It accelerates in jumps, and when the jump comes, the window closes faster than most leaders expected. The companies that find themselves scrambling to catch up in two years will be the ones that spent 2026 convincing themselves they had more time.
What Does Falling Behind on AI Adoption Actually Cost Your Business?
Falling behind on agentic AI adoption does not look like confusion about the technology. It looks like operational drag that compounds over time.
It means your competitors operate with fewer people handling repetitive, rule-based work. It means they respond to market changes faster because their reporting is automatic rather than manual. It means their cost structure is lower, their lead qualification is tighter, and their pipeline is cleaner. It means they are improving every week while your team is spending the same hours on the same tasks they were handling in 2021.
McKinsey's analysis of AI-mature companies found they are 3.4 times more likely to report significant revenue gains than companies still in early experimentation phases. That is not a forward projection. That is a gap already visible in earnings data from companies that made the move early.
In executive search and business development, we have watched this pattern play out across every major operational shift of the past thirty years. The companies that moved early on CRM adoption in the late 1990s built candidate and client pipelines that gave them market depth their slower competitors spent years trying to close. The companies that moved aggressively on digital sourcing after 2007 had candidate access that took an entire additional network-building cycle for laggards to replicate. Agentic AI is a larger shift than either of those. The compounding advantage is larger, and it accumulates faster.
"I may lose a battle, but I shall never lose a minute." That is Napoleon. The observation is two centuries old and it applies directly to where the Pittsburgh business market sits in 2026. The cost of waiting is not the cost of being wrong about AI. It is the cost of giving up time that cannot be recovered while competitors are compounding their advantage week over week.
[Wix blockquote: "I may lose a battle, but I shall never lose a minute." -- Napoleon]
The companies building right now are not ahead because they understand the technology better than everyone else. They are ahead because they decided to start before the outcome was certain.
What Does It Actually Take to Move From Experimenting to Building?
Moving from experimenting to building requires three things, and none of them are primarily technical.
The executives who feel most stuck on AI adoption are usually not confused about what agents do. They are overwhelmed by the scope of starting. Every week brings a new tool, a new framework, a new announcement. The space moves fast. It is easy to confuse watching the space with moving through it. The distinction between Group 2 and Group 3 is not knowledge. It is decision.
The first thing you need is a workflow audit. Identify five to ten processes in your business that are repetitive, rule-based, and time-consuming. These are the candidates for agent deployment. Lead routing and follow-up sequences. Client reporting and data aggregation across systems. Proposal generation. Scheduling and coordination. These are not the glamorous AI applications that appear in conference keynotes. They are the places where agent deployment generates real return in the first ninety days, and that return is what justifies the next phase of investment.
The second is a data readiness assessment. Agents work on your data. If your client records live in one system, your financial data in another, and your project tracking in a third, and none of these systems communicate with each other, agent deployment requires integration work before automation work can begin. This is not a reason to stop. It is a reason to start the assessment now so the integration work and the deployment planning happen in parallel rather than in sequence.
The third is an ownership decision. Who in your organization is accountable for driving this build-out? If the answer is everyone in general, the answer is no one in particular. The companies in Group 3 have a specific leader in the room who owns AI adoption, a VP of Operations, a COO, a technology director, with the authority and the accountability to push the build through organizational resistance and competing priorities.
In more than 30 years of retained search and business development across Western Pennsylvania, we have found that the companies that struggle most with major operational transitions are not the ones that lack the budget or the tools. They are the ones that lack internal ownership. The initiative stalls because no one has the mandate to keep it moving when it becomes difficult. Solving the ownership problem is step one. Everything else follows from it.
If the right internal leader does not exist yet, the alternative is a structured external partnership that brings both the technical deployment capability and the strategic direction until the internal capability is built. That is the model ProxiGee Services was built to deliver, placing both human and agentic resources into the specific workflows where the return is clearest and fastest.
PRL International is a retained executive search firm serving Pittsburgh and Western Pennsylvania, specializing in senior-level placements in energy, manufacturing, and industrial sectors. Through our partnership with ProxiGee Services, we help companies identify the right workflows, deploy the right resources, and build the organizational structure that sustains the advantage once it is established.
You Have Already Done the Work. Here Is What Comes Next.
If you have been reading this series, you already have the foundation. You understand what an agent is and how it differs from a simple automation. You understand what your data needs to look like before deployment makes sense. You understand workflow orchestration and what machine learning adds beyond basic rules-based automation. You understand the readiness criteria that separate companies that successfully deploy from the ones that invest, stall, and walk away frustrated.
You are already further along than most of your peers. The next step is not a technology decision. It is a business decision.
What comes next is not a purchase or a project scope document. It is a conversation about your specific business, your workflows, your data, your competitive position, and where the return on the first deployment is highest and fastest.
The window is still open. The early mover advantage is still available. Both of those statements are true today. Neither of them is permanent.
For more on how we place senior leaders for companies building operational capacity in Western Pennsylvania, read our mid-market executive search guide and why infrastructure companies are facing their most serious leadership gap in a decade.
If you are ready to fill a senior role or want to talk through your search, reach out at prlinternational.com/contact
Want to know what questions to ask before hiring a search firm? Download the free 7-Question Guide: https://prl-proposal.vercel.app/guide
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