Whitney Shaw is an executive coach and TEC Canada Chair in Edmonton. She runs peer advisory groups, manages a coaching practice, sits on two advisory boards, and co-founded a marketplace startup. Her fourth week of every month is back-to-back twelve-hour facilitation days.
“I hate written communication,” she told us during our first call. “Like I hate it with a passion. I hate sending follow-up emails. I hate drafting communications. I just always have.”
Her real bottleneck was not the facilitation days themselves. It was the aftermath: follow-up emails, action items, and communications scattered across five different systems (Google Tasks, Asana, PipeDrive, iPhone Notes, and verbal commitments). In her own words: “That's straight up ridiculous.”
We built her a workflow where she drops her Zoom meeting notes in and gets draft follow-up emails and consolidated action items back, pulled from one place instead of five. We also assembled a 15-page GTM strategy for her startup from 48 disconnected source files. The kind of synthesis work that is technically possible to do yourself, but almost nobody does.
None of this required enterprise-tier AI. No custom model. No six-figure implementation. Standard tools, configured around how she actually works.
The capability was already there. What was missing was the workflow architecture to make it useful. And the gap between “enterprise-grade” and “available to everyone” is closing faster than most business owners realize.
In November 2023, OpenAI launched a 128K context window at enterprise-tier pricing. Five months later it was standard across all tiers. Six months after that, competitors shipped it free. By March 2026, Anthropic made 1M-token context windows generally available at no premium. GitHub Copilot went from $19/user/month to a free tier in under 18 months.
Every feature that commands an enterprise premium today is on a clock. Inference costs are declining at a median rate of 50x per year according to Epoch AI's peer-reviewed analysis. Mid-tier AI models now match what was frontier-grade a year ago, at the same price they launched at. The enterprise tier is not disappearing. It is being compressed from below, faster than most procurement cycles can respond. (For the full data on where cost and performance are heading, see our analysis of the Mythos benchmarks.) Eighteen months ago, the AI capabilities Whitney's workflow runs on would have required an enterprise contract. Today they are standard-tier. In another eighteen months, they will be free.
Every model generation that ships while you do not have workflow architecture in place is a generation of compounding you do not get back.
Here is what that means concretely: Anthropic ships a major model release roughly every six to eight weeks. Each release improves the capabilities of every workflow built on top of it. Whitney's system was built in January. It has already absorbed three model upgrades without a single change to her setup. Each one made the output better. If she had waited until April to start, she would have the same tools available but none of the compounding.
The gap between early adopters and late movers is not static. It widens with every release. And releases are accelerating.
The businesses that will benefit most from where AI is heading in 2027 are the ones that have 18 months of workflow refinement behind them. They will know which processes work, which configurations produce the best output, and how to absorb a model upgrade in hours instead of weeks. That institutional knowledge does not compress. You cannot shortcut it by adopting later at a lower price point.
The model is the part that commoditizes. The workflow is the part that compounds. That advantage is not available to anyone who starts later and tries to catch up by paying less for a better model.