By Chuck Gallagher — Business Ethics Keynote Speaker and Trainer
TL;DR Research from SAS and IDC’s Data and AI Impact Report: The Trust Imperative found that organizations using AI primarily to cut costs earn the lowest return on investment of any AI objective group, while those focused on improving customer experience and expanding market share earn the highest. Chuck Gallagher, business ethics keynote speaker and AI speaker and author, argues that for small and medium-sized businesses, the pursuit of cost savings through AI is not just a strategic miscalculation — it is an ethical one, because it prioritizes organizational convenience over customer value.
A business owner I know adopted AI tools last year with one goal: reduce headcount. He replaced two customer service employees with a chatbot, saved roughly $80,000 in annual labor costs, and considered the project a success. Six months later, his customer satisfaction scores had dropped, two major accounts had left, and his team morale had cratered. He had cut costs. He had also cut the relationships his business ran on.
I am not telling that story to argue against AI adoption. I am telling it because it illustrates the central finding of the SAS and IDC Data and AI Impact Report with more precision than any statistic can. The report, which analyzed 2,375 organizations globally, found that cost reduction delivers the lowest ROI of any AI objective. Organizations that deploy AI to save money earn $1.54 in return for every dollar invested. Those that focus on improving customer experience earn $1.83 — nearly 20% more. That gap does not disappear at smaller scales. If anything, it widens, because SMBs are more dependent on customer relationships and have less margin to absorb the reputational cost of getting it wrong.
As an AI Speaker and Author, Here Is What the ROI Data Is Really Telling Us
As an AI speaker and author, I read the ROI findings in the SAS/IDC report not as a technology story but as an ethics story. The organizations chasing cost savings through AI are making a choice about what they value. They are choosing organizational efficiency over customer experience, short-term margin over long-term relationship, and measurable savings over harder-to-quantify trust. Every one of those tradeoffs has an ethical dimension that most business conversations about AI skip entirely.
The SAS and IDC report found that newer AI adopters — those with less than two years of experience — focus primarily on personal productivity, with 57% listing it as their top priority. But organizations with more than eight years of AI experience shift their focus to process efficiency and decision-making quality. The longer an organization works with AI, the more it understands that the technology’s real power is not in replacing human effort. It is in augmenting human judgment. That is a fundamentally different philosophy, and it produces fundamentally different results.
The report also found that organizations with more strategic AI goals — improving business resilience, expanding market share, enhancing customer experience — report significantly higher returns than those focused on cost reduction. The data point that matters most for SMBs: cost reduction ranks third in priority for AI newcomers and seventh for mature AI organizations. The companies that get the most from AI eventually stop chasing savings and start chasing outcomes. SMBs do not have to wait years to learn that lesson. They can learn it now, before the wasted investment.
What Happens When SMBs Treat AI as a Cost Tool Instead of a Strategy Tool?
When cost-cutting is the primary driver of AI adoption, several predictable failures follow. First, the wrong processes get automated. Cost-focused implementation tends to target the most visible expenses — usually labor — rather than the processes where AI can produce the greatest impact. Customer-facing interactions, where relationship quality drives revenue, are exactly the wrong place to start if cost reduction is your only lens.
Second, governance gets deprioritized. When the goal is savings, every dollar spent on oversight, training, and governance feels like it undermines the business case. The result is AI systems deployed without adequate accountability structures. The SAS and IDC report found that only about a quarter of organizations have a central group dedicated to AI governance. For SMBs, that number is almost certainly lower. And without governance, the risk exposure is not hypothetical — it is a matter of time and scale.
Third, and most consequentially, the wrong question gets asked. Cost-focused AI implementation asks “How much can I save?” The more productive question is “What outcomes do I want AI to help me achieve, and what would it take to use it responsibly toward those ends?” The SAS and IDC data makes clear that the second question leads to better financial outcomes, not just better ethics. The two are not in tension. They are aligned.
Three Strategic AI Goals That Outperform Cost Reduction for SMBs
The SAS and IDC report identifies customer experience improvement as the highest-ROI AI objective. For SMBs, this translates directly: use AI to respond to customers faster, more accurately, and more consistently, not to reduce the humans who serve them. AI tools that help a small business answer inquiries at midnight, personalize follow-up communications, or flag at-risk accounts before they churn create value that shows up in retention rates and referrals — both of which matter more to SMB revenue than labor savings.
Improving business resilience is the third-highest ROI category in the report, and it is dramatically underutilized among smaller organizations. Resilience-oriented AI uses the technology to identify vulnerabilities — supply chain disruptions, cash flow risk, customer concentration — before they become crises. For an SMB operating without the financial cushion that enterprises carry, early warning systems are not a luxury. They are a survival tool.
As a business ethics keynote speaker and AI speaker and author, the outcome I push hardest in conversations with SMB leaders is decision quality. AI that helps leaders make better decisions — with better data, better pattern recognition, and better scenario modeling — is AI that scales the judgment of whoever is running the organization. That is not cost reduction. That is capability amplification. And the SAS and IDC data suggests it delivers returns that cost-cutting never will.
Frequently Asked Questions
Q: Why does AI focused on cost savings produce lower ROI than other objectives?
A: According to the SAS and IDC Data and AI Impact Report, which measured ROI across thirteen different AI objective categories from a global survey of 2,375 organizations, cost reduction produces $1.54 in return per dollar invested — the lowest of all categories. Customer experience improvement produces $1.83 per dollar — nearly 20% higher. Cost-focused AI typically targets visible labor expenses, automates customer-facing interactions without adequate quality controls, and deprioritizes governance, all of which suppress long-term returns.
Q: What AI objectives produce the highest returns for businesses?
A: The SAS and IDC report found the top three ROI-producing AI objectives are improving customer experience ($1.83 per dollar), expanding market share ($1.74), and improving business resilience ($1.71). These strategic goals outperform operational objectives like reducing costs or increasing profits because they drive revenue growth rather than just margin improvement. Chuck Gallagher, AI speaker and author, notes that these objectives also align with the ethical imperative to use AI in ways that create value for customers, not just the organization itself.
Q: How do mature AI organizations differ from new adopters in their AI goals?
A: The SAS and IDC report found clear behavioral differences based on AI experience. Organizations with less than two years of AI experience prioritize personal productivity at a rate of 57%. Those with more than eight years of AI experience shift their focus to process efficiency (64%) and decision-making quality (60%). Mature organizations are also the only group that consistently prioritizes decision-making as a key AI objective — and they consistently outperform newer adopters in measured ROI.
Q: What is the most common AI mistake small businesses make?
A: The most common AI mistake small businesses make is treating AI primarily as a cost-reduction tool. The SAS and IDC Data and AI Impact Report found this approach produces the lowest measurable ROI of any AI objective. Small businesses that deploy AI to replace customer-facing human interaction without adequate oversight frequently see customer satisfaction decline, account attrition increase, and the short-term labor savings erased by long-term relationship damage. The better strategic frame is using AI to enhance what the business already does well.
Q: Do small businesses need AI governance if they are only using basic AI tools?
A: Yes. The SAS and IDC report found that governance is a key differentiator between organizations that realize transformational AI returns and those that see only marginal benefit. Even basic AI tools — chatbots, scheduling assistants, automated email responses — produce outputs that affect customers, employees, and vendors. Without documented oversight, accountability assignment, and output review processes, small businesses have no basis for identifying errors or defending their AI use if challenged. The scale of the tools does not reduce the need for governance. It reduces the cost of implementing it.
Share Your Thoughts
Here is the question I want you to sit with. When your organization adopted AI — or when you are considering doing so — what was the primary goal? Cost savings? Operational efficiency? Customer experience? I genuinely want to know, because the answer tells me a lot about where your risks are. Share your experience in the comments below, and I will respond personally. The five questions below are designed to push the thinking further.
Five Questions for Further Thought and Consideration
- If your AI investment is primarily justified by labor cost savings, what would you do if those savings were offset by measurable declines in customer satisfaction or retention?
- What would your best customer say about the experience of interacting with your AI-assisted processes? Would they feel better served or less served than before?
- If cost reduction is the lowest-ROI AI objective, why is it still the first thing most organizations reach for?
- What does it mean, ethically, to automate a process that was previously handled by a human being? Who benefits, and who bears the risk?
- How would you measure whether your AI tools are improving your organization’s capability to make better decisions, not just faster or cheaper ones?
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