How a 12-Person, 30-Year Merchandise Business Adopted AI

Looking at the Data: In the Greater West, 65.6% of employers use AI weekly. Only 38.5% of their employees do — a 27-point gap, the widest in TriNet's 2025 State of Work report. Eric Turney runs a 30-year-old, 12-person custom merchandise business across the Greater West region. His take: the gap isn't about trust or tools. It's about building the right tools that actually fit how the business runs.

Watch the full interview with Eric Turney →

In the Greater West, 65.6% of employers use AI weekly but only 38.5% of employees do — a 27-point gap, the widest of any U.S. region in TriNet's 2025 State of Work report.

AI doesn't fail because the tools are bad. It sometimes fails because the rollout assumes trust that might have not been built. 

According to TriNet’s State of Work reports, 27-point AI gap reflects the largest difference observed based on the reported data. But look at the rows underneath it: employers and employees worry about the same things at nearly identical rates. Empathy. Accuracy. Bias. That's not a trust gap: both sides distrust AI for the same reasons. What it actually points to is a permission and access gap. Employees haven't been given the tools, the workflows, or the green light to use AI the way their employers already do. 

How Turney built earned trust into the operating model

The Monterey Company is a 12-person custom merchandise business that's been at it for three decades. Long enough to have lived through three or four "everything changes" waves of new technology. AI is the first wave Turney is leading himself as owner and CEO — and the first he's treating like a real working partner inside the company, not just a tool to bolt on.

"I think you're late in the game if you're not adopting at least simple AI models to help automate your system. Even service-based businesses or local businesses, plumbers, construction — I think there's an adoption for AI everywhere in small businesses these days."* — Eric Turney

Turney's philosophy is simple: AI supports how the business actually grows, so it gets the same level of care as any new hire or new process. The leadership team builds and tests the workflow first. They check that the data going in is clean. They confirm the tool does what it's supposed to do. Only then does it land in front of the team.

"If the data is not accurate — we've totally seen that, and I've even been a victim of that too where it gets overloaded with data — and then people are just: 'I'm done, this doesn't work.'"* — Eric Turney, on building trust with his team around AI

That second piece is the one most SMBs underestimate. Roll out a tool that hallucinates once, and the team writes it off forever. Trust is much harder to rebuild than to earn the first time.

"As long as I have the system dialed and this is exactly how I do it, and make a good workflow, then adoption is usually pretty quick and painless."* — Eric Turney

Why the Greater West's AI gap exists

The State of Work data shows employers and employees worry about AI at nearly identical rates. The three concerns are worth unpacking, because each one is exactly what Turney is solving for when he builds the workflow before rolling out the tool.

• Lack of empathy(36.6% of employers, 36.5% of employees rate this an "extreme concern"). AI doesn't read a room. It doesn't know that a longtime client wants a phone call instead of an email, or that a custom merchandise order with a personal note hits differently than a templated reply. In a 30-year business built on relationships, the empathy gap isn't theoretical — it's the brand. The fix isn't avoiding AI. It's keeping AI on the parts of the work where empathy isn't the differentiator.
• Data accuracy(33.3% of employers, 38.5% of employees rate this an "extreme concern"). This is the concern Turney named directly. Overload a model with messy data and the output gets unreliable fast. Hand an unreliable tool to a team, and they walk away from it inside a week. Most SMBs without dedicated data hygiene are one bad rollout away from a permanent adoption ceiling.
• Bias (30.4% of employers, 34.6% of employees rate this an "extreme concern"). Hiring tools, performance summaries, customer segmentation — every AI system trained on past behavior risks repeating patterns the company has spent years correcting. SMBs without data science benches typically can't audit for this on their own. The mitigation is keeping a human in the loop on every decision the tool touches, and being specific about which decisions those are.

Turney's model addresses all three directly: don't roll out tools faster than the team can integrate them, and don't ask the team to trust the company's AI judgment before the company has earned the right to ask for it.

Why this matters for SMB operators in the Greater West

The State of Work data and Turney's playbook converge on a specific operator reality across Alaska, Arizona, Colorado, Idaho, Kansas, Nebraska, Nevada, New Mexico, Oregon, South Dakota, Utah, Washington, and Wyoming:

•      A 27-point AI gap signals a possibly workflow-fit problem, not necessarily a trust problem. The tools were chosen for employer use cases, not employee workflows. Adoption follows fit.

•      Onboarding is a high-leverage moment for AI rollout. New employees onboarded into AI-integrated workflows can generally adopt faster than tenured employees retrofitted into them. Every quarter of delay costs that compounding curve.

•      Employee Benefits design should align with the universal-priority areas. Medical insurance, paid time off, mental health coverage, and parental leave are the strongest agreement areas between Greater West employers and employees — and the highest-return retention investments.

•      Multi-state HR Compliance is real infrastructure work. Washington, Oregon, and Colorado have more developed employment-related requirements. Wyoming and South Dakota are comparatively lighter. An SMB operating across three or more Greater West states, the compliance demands typically warrant HR outsourcing or a PEO engagement — not as a perk, but as core support for a lean team.

How to put this into practice

For Greater West operators rethinking AI adoption:

1.     Don't roll out AI tools across the team in one wave. Map your team's roles, functions, and adoption readiness, then tier the rollout. The wrong tool in the wrong workflow poisons future adoption.

2.     Consider  AI-powered training in onboarding. In our experience, teams that start with  AI-enabled workflows tend to adopt them more quickly than those integrating them later. Lock in that compounding effect from day one.

3.     Audit your AI tools against the workflows that matter. If the tool was chosen because it ranked well in a buyer's guide and not because it fits your team's actual work, you'll see exactly the kind of adoption gap the State of Work data captures. Plan for AI adoption with specificity to your industry, your goals, and your existing tech stack.

What's next for Greater West SMBs

The State of Work data describes a region with engaged employees, real workload tension, and an AI adoption gap that's wider than the headlines suggest. The operators closing the gap aren't the ones buying more tools — they're the ones treating AI rollout the same way they treat any other addition to the team's working life: earned, calibrated, and on a timeline that respects how trust actually builds.

Read the full Greater West regional report from TriNet's 2025 State of Work →

Operating across WA, OR, and CO? See how TriNet supports HR outsourcing, multi-state compliance, and benefits →

FAQ

What's the AI adoption gap in the Greater West region?

TriNet's 2025 State of Work report found 65.6% of Greater West employers use AI weekly or more, while only 38.5% of their employees do — a 27-point gap, the widest of any region in the report.

Why don't employees in Greater West states use AI as much as their employers?

The State of Work data shows it's not a trust gap. Both groups share nearly identical concerns about AI's lack of empathy, accuracy, and bias. The gap is closer to a permission and workflow-fit problem — tools were often chosen for employer use cases, not employee workflows, and rollout timelines outpaced integration.

How should small businesses in Colorado, Washington, or Oregon consider when using AI?

The pattern that worked for Eric Turney at The Monterey Company treats AI rollout like onboarding rather than infrastructure. Leadership builds and tests the workflow first, validates data accuracy, then hands the tool to the team once it's reliable.

What are the biggest AI concerns small businesses share?

Lack of empathy, data accuracy, and bias — all three rated at "extreme concern" by roughly a third of employers and a third of employees in the Greater West region. The concerns are similar across both groups, which is why the adoption gap reads as access-related rather than trust-related.

What HR Compliance issues do multi-state Greater West employers face?

The 13-state region varies dramatically. Washington, Oregon, and Colorado have more developed employment-related requirements (paid leave, wage transparency, scheduling rules). Wyoming and South Dakota are comparatively lighter. An SMB operating across multiple Greater West states faces real compliance demands — which is why HR outsourcing is common in this footprint.

What Employee Benefits matter most in the Greater West?

The State of Work report identified four areas where Greater West employers and employees are aligned: medical insurance, paid time off, mental health coverage, and parental leave. These are the strongest agreement areas in the entire regional dataset — and the highest-leverage Employee Benefits investments for retention.

Should small businesses in this region use HR outsourcing?

For multi-state operators, yes. The compliance asymmetry between Washington, Oregon, and Colorado on one end and Wyoming and South Dakota can create complexity for multi-state employers. As headcount grows, especially past 25–30 employees, some organizations may find that HR outsourcing or a PEO provides helpful support with these obligations more efficiently.