
Michigan businesses learned a hard lesson in 2025.
AI is easy to buy. Value is much harder to create.
As we head into 2026, the conversation needs to shift. This is no longer about which AI tool is best. It is about strategy, ownership, governance, and readiness for what comes next.
Below is a practical, business-first look at what worked, what failed, and how owners and managers should be thinking about AI going forward.
Buying AI tools without a strategy.
Many SMBs spent thousands per month on AI subscriptions that delivered little value. The common problems were buying tools before defining the business problem, selecting enterprise tiers for very small teams, and having no one accountable for usage or ROI.
AI agents are autonomous systems that understand goals, plan steps, and take action on your behalf.
Unlike 2025 chatbots that waited for instructions, AI agents can run entire workflows such as invoice follow-ups, document routing, or client intake with limited human involvement. In 2026, this allows small firms to operate with the efficiency of much larger organizations.
Most SMBs should start in the $20 to $50 per user, per month range.
Testing adoption at a low cost reveals who actually uses the tools and where value exists. Firms that jumped straight into expensive plans often discovered that only a handful of people ever logged in.
Not usually.
Most SMBs cannot justify a full-time AI hire. Better options include assigning AI ownership to an existing leader with budget authority, or partnering with an IT provider that already understands AI, compliance, and governance.
Cyber insurance carriers are now asking about AI governance.
Using free consumer AI tools with client or patient data can void coverage. Businesses need documented policies that define approved tools, data handling rules, human review requirements, and incident response expectations.
If 2025 taught Michigan businesses anything, it is this.
Buying AI tools is easy. Getting value from them is hard.
Over the past year, I watched accounting firms, law firms, medical practices, and manufacturers across Michigan rush into AI with good intentions. The results ranged from modest wins to expensive disappointment.
A Birmingham firm discovered it was spending nearly $3,000 per month across seven AI tools. The actual business value was closer to $300. The rest was shelfware, unused features, and enterprise licenses for teams of three.
Year-end reviews uncovered subscriptions no one remembered approving. Tools tied to former employees’ cards. Team plans sized for 20 users where only two people ever logged in. Many firms were quietly bleeding $500 per month or more.
That free AI account someone used to summarize client documents is not just a security issue. It is an insurance liability. Carriers now ask directly about AI governance, and “we didn’t know” is no longer an acceptable answer.
AI was supposed to save time. Instead, some teams spent more time learning tools, correcting AI errors, managing subscriptions, and training reluctant users than they ever saved.
The firms that succeeded shared a few clear traits.
They started with the problem, not the product.
Instead of debating tools, they asked where time or money was being wasted each week.
They tested cheap first.
Low-cost trials revealed real adoption. Expensive licenses did not fix lack of usage.
They assigned ownership.
One person with budget responsibility owned AI decisions and could cancel tools that failed to deliver value.
They kept humans in the loop.
Client-facing work was reviewed. Research was verified. Communications were edited. Firms that skipped this step learned painful lessons.
This is where the shift happens.
2025 was the year of AI tools.
2026 will be the year of AI agents.
AI agents do not just answer questions. They understand objectives, plan multi-step actions, and execute tasks across systems with oversight.
Instead of asking AI to draft a single overdue invoice email, an AI agent could:
Check your accounting system for overdue balances
Review client payment history
Draft a message based on the relationship
Schedule delivery at the right time
Follow up automatically
Escalate to a human when judgment is required
Major platforms including Microsoft, Google, and Salesforce are actively building these capabilities. Industry analysts like Forrester predict rapid adoption across HR, finance, and operations.
The opportunity
Smaller firms can operate at a scale that once required more staff. Tasks that were delayed or ignored can be handled consistently and efficiently.
The risk
Without governance, AI agents can make mistakes faster and at greater scale. They can access systems they should not. They can act without proper approval. They can expose data in ways that put insurance and compliance at risk.
Most Michigan SMBs face a simple reality.
You need AI expertise, and you probably do not have it internally.
Your IT team is already managing security, compliance, cloud platforms, vendors, and daily support. Adding AI strategy on top of that is not realistic.
Option 1: Hire an AI lead
Effective but expensive. Rarely practical for most SMBs.
Option 2: Figure it out internally
Common, but risky. Learning happens in real time, and mistakes can be costly.
Option 3: Partner with an experienced IT advisor
Work with a partner that already understands AI, compliance, and governance. Someone who focuses on outcomes, not shiny tools.
This is where Big Water Technologies helps. Our role is not to sell AI for AI’s sake. It is to help Michigan businesses apply it safely, responsibly, and profitably.
Review credit card statements and cancel anything without a clear owner or measurable value.
One person must own approvals, policies, and results.
Focus on repetitive work, error-prone processes, and areas where speed creates competitive advantage.
AI agents depend on clean, connected data. If systems do not talk to each other, AI will not deliver reliable results.
AI is not slowing down. It is accelerating.
The firms that win in 2026 will not be the ones with the most AI tools. They will be the ones with clear strategy, strong governance, and disciplined execution.
If your AI plan today is “let’s buy another tool,” it is time to pause.
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