A three day AI build saved a logistics company $180K per month and turned into nearly seven figures in ARR. That’s not a flex. It’s a signal that outcome based pricing and AI leverage are rewriting how professional services firms compete.
A simple, repeatable plan to pick wins, launch pilots and measure impact.
You don’t need a lab or a giant budget to start. You need a clear why, a short list of high-impact problems, and a fast way to test. Here’s the formula I’ve used for my company and clients that you can run as a visionary founder or owner to build your “getting started” roadmap.
How much of your hesitation around AI is about real risk—and how much is about uncertainty?
Lately, I’ve had a lot of conversations with other founders about privacy and IP in the age of AI. Most are worried. They fear exposing client data, losing control of their IP, or stepping into a legal gray zone they don’t fully understand. Those are real concerns. But here’s the thing: every transformative technology starts this way: undefined, messy, and full of opportunity for the ones who move first.
CEO’s are putting a lot of pressure on their organizations to “adopt artificial intelligence.” Often it stems from a board mandate. But few know what it means to “adopt” and recent data from MIT proves this point.
Are you still building your consulting practice on the traditional pyramid model while your competitors race toward AI-powered transformation? Here’s a wake-up call: the consulting industry has fundamentally changed. While you’re optimizing billable hours and adding junior analysts, forward-thinking firms are already leveraging AI-amplified expertise to deliver five times the value without increasing their overhead.
In professional services, we pride ourselves on solving complex problems with smart people. But when it comes to adopting artificial intelligence, the constraint is rarely the technology; it’s us. Research shows that people resist, and sometimes even sabotage, AI initiatives. CIO.com, reported in the Pivot 5 newsletter, released a study revealing that 31% of workers (including 41% of Millennials and Gen Zs) are actively undermining their company’s generative AI rollout.
Most cybersecurity leaders have embraced AI’s obvious benefits. You’ve automated log reviews, accelerated threat detection, and improved incident response times. Your dashboards look impressive, and your team feels more efficient.
Your calendar assistant nudges an internal meeting 15 minutes later. An AI tax module files the firm’s quarterly return with a digit off. Both lean on AI. One slip just shuffles a coffee break; the other invites the IRS and torches your reputation. So which jobs can roll on autopilot and which stay human-led?
Your business is growing fast. But your bookkeeping is not keeping up. Reports are late and disjointed. Mistakes are increasing. You’re working too hard to get basic financial data. Sound familiar? Here’s what most business owners don’t realize: You may not need another bookkeeper anymore. AI can now handle many bookkeeping tasks. Instead of posting job ads and training new hires, it may be time to explore a completely different solution to your bookkeeping problems.
Ever since artificial intelligence (AI) became widely accessible and democratized just a couple of years ago, a wave of uncertainty swept across professional service firms. The prevailing concern was clear: Will AI replace us? Will clients simply turn to AI tools instead of hiring experts who have spent years mastering their craft?