BTR: SMB Leaders Must Balance Innovation and Risk to Navigate AI Era

Christopher Miller, ATB Technologies

SILVER SPRING, MD, UNITED STATES, July 2, 2025 /EINPresswire.com/ -- The AI revolution is no longer confined to the Fortune 500. With copilots, chatbots, and machine learning tools becoming increasingly accessible through mainstream productivity suites and cloud platforms, small and midsize businesses (SMBs) are confronting a new set of strategic, operational, and technological decisions—many without the internal expertise typically found in enterprise environments.

A recent BizTechReports executive vidcast with Christopher Miller, Vice President of Sales and Marketing at ATB Technologies, reveals how SMBs—particularly in sectors like manufacturing, engineering, and nonprofit services—are approaching this transition. The conversation highlights a growing realization: while AI promises significant productivity gains, its adoption introduces real risks that many SMBs are not yet equipped to manage.

Productivity Without Headcount Expansion

SMBs are exploring AI not to cut headcount, but to stabilize it. In the current labor market, hiring remains a challenge, especially for roles requiring technical skill or business analysis. Many small business leaders see AI as a means of achieving “growth without hiring”—using automation to relieve employees of repetitive tasks, surface strategic insights, and increase the capacity of teams without expanding payroll.

This shift is more necessity than luxury. A recent report from Gartner projects that by 2026, 80% of small and medium enterprises will use AI-enhanced applications to augment or automate key business functions, driven by a desire to stay competitive without overextending budgets.

However, as Miller notes, many SMBs lack a clear starting point. “Leaders hear the term AI, but the question they’re really asking is: what do I do with it, and what does it mean for my people?” he said.

Early Gains Come from Horizontal Use Cases

While industry-specific applications of AI are still nascent in the SMB space, early wins are coming from horizontal functions—especially in marketing, human resources, and customer support. Use cases include:

* AI copilots summarizing email threads and surfacing missed tasks after PTO

* Generative tools drafting job descriptions and marketing copy

* HR teams leveraging transcription and sentiment analysis to evaluate candidate interviews more efficiently

“In these cases, AI is helping organizations focus their people on what they do best,” Miller observed. “It’s not replacing humans—it’s reducing noise and increasing bandwidth.”

That perspective aligns with broader SMB adoption trends. According to a 2024 IDC report, SMBs are already deploying AI for content generation, customer interaction, and basic analytics, with 64% of respondents citing “efficiency gains” as the top motivator.

Yet even as usage grows, AI remains largely ad hoc in SMB environments—deployed as tactical tools rather than woven into long-term business strategy.

Low-Cost Entry, High-Stakes Risk

One factor driving AI experimentation among SMBs is its increasingly low barrier to entry. Platforms like Microsoft 365 and Google Workspace now include embedded AI features that can be accessed for minimal incremental cost. Similarly, tools like ChatGPT or Jasper can deliver real business value for less than $50 per user per month.

But while the upfront costs are low, downstream risks—particularly in terms of data governance and exposure—are high. “What seems like a free tool today can become very expensive tomorrow if it leaks customer data or exposes IP,” Miller warned.

The absence of formal IT governance structures compounds the problem. Unlike enterprises, which often employ CISOs and legal teams to shape AI policy, SMBs typically operate without formal guardrails. “We’re seeing employees copy-paste sensitive information into public tools,” Miller said. “They’re not doing anything malicious—they just don’t realize what’s at stake.”

The observation is supported by the analyst community. A 2024 study by ISG (Information Services Group) found that 72% of SMBs have no formal AI policy in place, while 39% reported at least one incident of unintentional data leakage linked to an AI tool.

Cloud Delivery, Data Privacy, and the Vertical Frontier

Most SMBs are consuming AI as-a-service via SaaS platforms—mirroring the cloud adoption curve of the previous decade. Miller believes this pattern will persist. “They’re not standing up GPU clusters,” he said. “They’re using data centers and SaaS-based copilots.”

But new challenges loom. As demand for generative AI and large language models increases, so does the strain on power grids and data infrastructure. While this seems like a problem for hyperscalers, the ripple effects—like higher energy costs or data center congestion—could impact small businesses disproportionately.

“We’re entering a phase where the cost of power becomes part of the digital transformation conversation,” Miller noted. “MSPs have a role to play in helping SMBs manage that transition efficiently.”

Meanwhile, the market is beginning to move from horizontal use cases to vertical-specific applications—an area ripe for development. For example, Miller described a client in the liquid manufacturing space that used AI to optimize delivery routes, reducing wasted trips and improving customer satisfaction. “It wasn’t about data science,” he said. “It was about solving a real operational bottleneck.”

This reflects a broader trend in AI maturity. “Phase one was general productivity. Phase two is industry-specific optimization,” Miller said.

Governance and the Role of MSPs

For most SMBs, MSPs are the de facto IT department—placing them in a unique position to guide responsible AI adoption. Miller emphasizes the importance of moving from reaction to planning. “Employees are going to use AI. The only question is whether there’s a policy in place when they do,” he said.

This makes education and policy formation urgent. “If you don’t pay for the product, you are the product,” Miller noted. That insight, often repeated but seldom operationalized, is particularly relevant as AI tools evolve in complexity and opacity.

MSPs can also play a proactive role in use case development. By aligning AI capabilities with specific business pain points, they can help clients prioritize investments and monitor impact. “We’re not just installing tools,” Miller said. “We’re helping build strategy.”

A Narrow Window for Strategic Differentiation

AI adoption in the SMB sector is accelerating, but the window for differentiation is narrow. SMBs that adopt AI tactically—without a governance framework—may achieve short-term gains but risk long-term vulnerabilities. Conversely, those that take a disciplined, human-centered approach to adoption may unlock competitive advantages that scale with their business.

The key, according to Miller, is intentionality. “Start with your business challenge,” he advised. “Then figure out how AI can help. Not the other way around.”

The future of SMB competitiveness will be shaped not by who has access to AI—but by who uses it well, securely, and strategically. And in that equation, trusted MSPs and clear policies may matter as much as the tools themselves.

Click Here to Read a full Q&A of this Interview.

Airrion Andrews
BizTechReports
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