Stop looking for AI projects, start improving your processes

David Zey Gerry Pitt

July 27, 2026

Artificial intelligence has become one of the most talked-about topics in business.

Every week seems to bring another AI-powered tool promising to increase productivity, reduce costs or transform the way organizations work.

For small and mid-sized businesses (SMBs), the pressure to “do something with AI” has never been greater.

Unfortunately, many organizations begin their AI journey the wrong way.

They purchase a chatbot, experiment with AI-generated marketing content or ask employees to use AI to summarize meetings.

Though these tools can save a few minutes here and there, they rarely deliver the transformational return on investment that business leaders expect.

The companies seeing meaningful results are asking a different question.

Instead of asking, “Where can we use AI?” – they ask, “Which business process is slowing us down the most?”

That subtle shift changes AI from another technology purchase into a business improvement strategy.

AI is not the strategy, better processes are

For decades, organizations have relied on proven continuous improvement methodologies such as Lean, Six Sigma and the Plan-Do-Check-Act (PDCA) cycle to eliminate waste and improve quality.

Those approaches remain just as relevant today.

What has changed is AI’s ability to accelerate them.

Too often, businesses automate individual tasks instead of redesigning entire workflows.

Automating a single activity may save a few minutes, but it doesn’t remove the delays, bottlenecks and handoffs that prevent work from flowing efficiently across the organization.

Consider a few common examples:

• Using AI to write emails faster
• Generating marketing copy
• Summarizing meeting notes
• Drafting job descriptions

These are useful productivity gains, but they don’t fundamentally improve how the business operates.

Now consider a purchasing process that requires multiple manual approvals, duplicate data entry and employees searching through emails for supporting information.

If AI can streamline the entire approval workflow, automatically gather relevant information, flag exceptions and notify stakeholders, the organization saves far more than minutes.

It can shorten cycle times, improve visibility and reduce costly delays.

However, improving one step in the process can simply shift the bottleneck downstream. 

Purchase orders may move through approvals much faster, only to become backed up in fulfillment because that part of the workflow hasn’t been improved.

True process improvement requires examining the entire end-to-end value stream, ensuring each enhancement creates flow rather than simply relocating the constraint.

The biggest opportunity isn’t making individual employees faster.

It’s making the entire business run better.

AI accelerates continuous improvement

Business leaders don’t need to abandon the process improvement disciplines they’ve spent years building.

AI simply strengthens each phase of the improvement lifecycle:

Discover the real problems

Every organization collects enormous amounts of information from customers and employees.

Surveys, support tickets, meeting notes, emails, production reports and customer feedback often contain valuable insights.

However, reviewing all of that information manually takes significant time.

Despite the talk about clean data, AI can analyze thousands of pages of unstructured information in minutes, identifying recurring themes, common complaints and emerging trends that might otherwise go unnoticed.

Instead of relying on assumptions, leadership gains a clearer understanding of where employees struggle and where customers experience friction.

Analyze the process

Traditional process mapping often involves interviews, workshops, sticky notes and whiteboards.

Though those exercises remain valuable, AI-powered process analysis can provide a much more objective view.

Modern process mining tools analyze system event logs to visualize how work actually moves through the organization, not how people think it moves.

When using AI helps identify the right work, the results often surprise leadership teams.

AI can quickly identify:

• Repeated bottlenecks
• Excessive approval steps
• Manual rework
• Duplicate data entry
• Process variations between departments
• Root causes of recurring delays

Instead of debating opinions, teams can improve processes using real operational data.

Redesign with confidence

Once bottlenecks are identified, AI becomes an excellent brainstorming partner.

Rather than spending days developing multiple improvement scenarios, AI can rapidly generate alternative workflows, estimate timelines and effort, identify potential risks and recommend process improvements based on organizational goals.

This doesn’t replace the expertise of your employees.

Instead, it gives them a stronger starting point.

It is often easier for people to critique a plan than to create one from scratch, and plan refinement often leads to better outcomes.

Rather than beginning with a blank page, employees evaluate, refine and improve AI-generated recommendations using their experience and knowledge of the business.

Monitor and improve continuously

Continuous improvement shouldn’t happen only during annual planning sessions.

AI enables organizations to monitor operations continuously.

Instead of waiting for monthly reports or quarterly business reviews, AI can detect anomalies in real time, including quality issues, inventory discrepancies, customer service trends or financial exceptions.

Using the same data sources and logs to identify the issues also enables measurable signals for AI to track and show improvement.

This allows organizations to respond to problems while they’re still small instead of after they’ve become expensive.

The human side of AI matters most

Despite all the attention given to AI models and algorithms, successful AI initiatives are rarely technology projects.

They are change management projects.

Employees naturally have concerns when AI is introduced into the workplace.

Some worry about job security.

Others question whether they can trust AI-generated recommendations or believe they need advanced technical skills to use these tools effectively.

Leadership plays a critical role in shaping that conversation.

The objective should never be to replace talented employees.

The goal is to eliminate repetitive, low-value work so employees can spend more time solving problems, serving customers and making informed business decisions.

One of AI’s greatest strengths is eliminating “blank page” work.

Instead of creating reports from scratch, researching information manually or building spreadsheets one formula at a time, employees begin with a solid first draft generated by AI. 

This shift dramatically reduces the time spent creating initial content while allowing employees to focus their expertise where it adds the most value: validating information, applying business context, exercising judgment and making better decisions.

AI doesn’t replace human creativity.

It eliminates the friction of getting started, allowing people to spend more time improving ideas rather than inventing them from scratch.

Their role shifts from creator to reviewer, strategist and decision-maker.

That transition increases both productivity and job satisfaction.

However, organizations should resist the temptation to remove humans entirely from important business decisions.

The most successful implementations follow a human-in-the-loop model.

AI provides recommendations – people provide judgment.

Business leaders still evaluate context, customer relationships, ethics, regulatory requirements and strategic priorities before making final decisions.

AI supports better decisions – it doesn’t replace leadership.

Where should SMBs begin?

Many executives feel overwhelmed by the number of AI products entering the market.

Rather than launching a broad AI initiative, start with a single business process.

Ask questions such as:

• Which workflow frustrates employees the most?
• Where do customers experience unnecessary delays?
• Which process consumes the greatest amount of administrative time?
• Where do we repeatedly perform the same manual work?

High-impact opportunities often include invoice processing, purchase approvals, customer service requests, sales proposal development, employee onboarding, inventory planning and production scheduling.

Choose one process that affects multiple employees, has measurable outcomes and creates noticeable friction.

Improve that process first, measure the results and then expand to the next opportunity.

Small, measurable successes create organizational confidence and encourage broader adoption.

Process first, AI second

The businesses that gain the greatest competitive advantage from AI won’t necessarily own the newest technology or deploy the largest number of AI tools.

They will have the most efficient business processes.

For SMB leaders, AI should be viewed as a business improvement capability rather than a standalone technology investment.

When combined with proven continuous improvement practices, AI helps organizations remove friction, accelerate decision-making, improve quality and empower employees to focus on work that creates real value.

Before approving your next AI investment, pause and ask one question: “What business process is costing us the most time, money or customer satisfaction?”

Start there.

When AI is applied to improve the way work flows across the organization, not simply to automate isolated tasks, it becomes far more than a productivity tool.

It becomes a catalyst for operational excellence and long-term competitive advantage.