By Tim Finerty
Artificial intelligence has quickly moved beyond experimentation. Across the industrial automation sector, organizations are using AI to streamline workflows, improve decision-making, and uncover new opportunities for efficiency and growth.
Yet the real opportunity isn’t found in isolated tools or one-off projects. As AI becomes increasingly embedded in business operations, industrial automation firms face a larger challenge: Determining how to adapt their organizations to remain competitive in a rapidly changing environment.
Success will depend less on adopting the latest technology and more on developing a practical strategy that aligns AI with business goals, workforce capabilities, and operational priorities.
AI is Becoming a Competitive Differentiator
Industrial automation organizations are under constant pressure to improve productivity, respond more quickly to customer needs, and make the most of limited resources. At the same time, many firms continue to grapple with workforce shortages and the loss of institutional knowledge as experienced employees retire.
AI offers an opportunity to address many of these challenges.
Organizations that effectively integrate AI into their operations can reduce time spent on repetitive tasks, accelerate decision-making, and enable employees to focus on higher-value work. The benefit isn’t replacing people — it’s allowing skilled professionals to spend more time solving problems, serving customers, and driving innovation.
Whether it’s assisting with proposal development, generating documentation or organizing information, AI can help teams work more efficiently without fundamentally changing their roles.
Data Readiness Matters More than Technology
While many organizations have begun experimenting with AI, relatively few have established the foundation needed to scale their efforts.
The reason is simple: AI is only as effective as the data available to it.
Most industrial automation firms operate across multiple systems, including ERP platforms, CRM applications, project management tools, engineering software and operational technologies. When those systems don’t communicate effectively, valuable information remains fragmented and difficult to access.
Disconnected data limits the impact of AI initiatives, making it harder to automate processes, generate reliable insights, and support informed decision-making.
Before investing heavily in advanced AI capabilities, organizations should evaluate the quality, accessibility, and consistency of their data. In many cases, strengthening that foundation will create more value than implementing additional AI tools.
Custom Solutions Are Creating New Opportunities
Many organizations begin their AI journey by exploring capabilities already embedded within existing software platforms. That’s a sensible starting point.
However, recent advancements have also made it easier to develop tailored solutions that address specific business challenges.
Rather than relying exclusively on off-the-shelf applications, organizations can increasingly use AI-assisted development tools to build custom workflows, automate repetitive activities, and create solutions aligned with their unique operations.
This flexibility is especially valuable for firms whose work processes are highly specialized or project-driven. Customized tools can often deliver greater efficiency while avoiding the costs and compromises that come with adapting business processes to standardized software.
Where AI is Delivering Value Today
While priorities vary across organizations, several use cases are emerging as particularly impactful.
- Knowledge retention. Many firms are exploring ways to preserve expertise accumulated over decades. AI can help organize and make institutional knowledge more accessible, reducing the risk associated with employee turnover and retirement.
- Project and proposal support. AI can help accelerate proposal development, summarize requirements, organize project information, and streamline documentation, enabling teams to focus on more strategic activities.
- Operational insights. By analyzing large volumes of data, AI can help identify trends, improve forecasting, and support more informed business decisions.
- Customer and service support. AI-powered assistants can help employees quickly locate information, respond to inquiries, and access relevant documentation when needed.
Think Big, Start Small
Organizations often make the mistake of pursuing large-scale transformation before establishing clear objectives or proving value.
A more effective approach is to start with focused initiatives tied to specific business challenges. Small pilot projects create opportunities to learn, measure outcomes, and build internal confidence while limiting risk.
Over time, successful pilots can inform a broader strategy and help organizations identify where AI can create the most meaningful impact.
The goal is not to implement AI for its own sake. It is to solve problems, improve performance, and strengthen the organization’s ability to adapt to changing market conditions.
Adaptability Will Define Future Success
AI is reshaping how organizations operate, compete and deliver value. While the pace of change remains uncertain, the direction is increasingly clear.
Industrial automation firms do not need to reinvent themselves overnight. They do, however, need to begin building the capabilities, processes, and data foundations that will help them navigate an AI-driven future.
The organizations that approach AI thoughtfully today will be better positioned to improve efficiency, empower their workforce, and respond to whatever comes next.
In an environment defined by continual change, adaptability may become the most important competitive advantage of all.
Tim Finerty, CPA, is a partner with Wipfli Advisory LLC. WIPFLI partners with CSIA to provide members with business and tech advisory services from a firm that understands your unique business needs.
Photo by Campaign Creators on Unsplash