Small and medium-sized enterprises (SMEs) are rapidly adopting AI tools like ChatGPT and Copilot to streamline workflows and boost productivity. According to SME News, many UK SMEs already experiment with AI in isolated pockets, from automating customer emails to generating reports. However, there remains a significant gap between mere AI usage and meaningful process redesign that fully leverages automation's potential.
Bridging this gap requires more than just access to AI-powered tools; it demands an automation mindset within the team, a clear strategy for staff selection, and deliberate upskilling efforts. This blog post explores how SMEs can identify and develop the right employees to champion AI automation projects, avoiding the common pitfalls of missing project ownership or relying solely on new hires.
Why Upskill Instead of Hiring New Specialists?
AI Global Media's recent feature (see related info at imgcdn.aiglobalmedia.net) highlights how SMEs often face budget constraints and cultural challenges when hiring external AI specialists. On the other hand, training existing staff:
- Leverages deep operational knowledge held by current employees Fosters continuous improvement as automated processes affect core workflows Enhances employee engagement and retention through career development Accelerates adoption by having respected project leaders embedded within teams
However, successful upskilling for automation mindset requires careful staff selection rather than a blanket approach. Not every employee will thrive in interpreting AI outputs, redesigning handoffs, or troubleshooting automated workflows.
What Changed in the Workflow? Understanding the Foundation Before Upskilling
Before investing in any training or tools, always ask, "What changed in the workflow?" SMEs frequently adopt AI tools like ChatGPT or Copilot as isolated add-ons without redesigning processes they support. For example, automating report generation is not just about tool use — it involves:
Identifying which report templates require updating Clarifying who approves automated drafts Defining exception handling when outputs are inaccurate Reassigning tasks that become redundant to free up capacityOnly after these changes are mapped out can appropriate upskilling happen. This avoids investing in training people on tools while the underlying process remains inefficient or unclear.
Key Traits to Look for in Employees to Upskill
When selecting candidates to lead or support AI automation projects, focus on skills and mindsets beyond technical ability alone. Important criteria include:
Trait Why it Matters How to Spot it Curiosity and Adaptability Employees must be willing to experiment with AI tools and adapt workflows as needed. Look for early AI adopters or those who ask questions about process improvements. Process Understanding Deep knowledge of existing workflows enables redesigning handoffs and approvals effectively. Identify staff who frequently map or optimise processes, or who manage cross-team interactions. Collaboration and Communication AI automation projects require input from multiple teams and roles. Choose people who naturally liaise across departments and lead meetings or updates. Problem-Solving Attitude Key for troubleshooting AI outputs and refining templates or decision trees. Note those who proactively identify bottlenecks and propose fixes. Ownership and Accountability Successful automation projects thrive on clear leadership and ongoing monitoring. Select individuals who take responsibility for results and follow through.Balancing Project Leadership and Team Involvement
Another critical aspect is designating clear project leadership for AI automation initiatives. The Southern Enterprise Awards 2026 have recognised the value of strong AI project champions within SMEs who balance hands-on problem solving with broader governance oversight.
Consider appointing an AI Automation Lead or Automation Champion drawn from your upskilled staff pool who can:
- Coordinate trainings and tool adoption in their business unit Serve as the first point of contact for process-related change requests Monitor performance metrics and feedback loops for automated workflows Ensure compliance with internal policies and data governance standards Liaise with external experts only when highly specialised input is necessary
This leadership role helps prevent fragmentation and dilutes responsibilities that often derail automation efforts.
Crafting a Practical Upskilling Plan
Once you identify candidates and confirm workflow changes, design an upskilling programme tailored for AI automation. Elements to include:
Foundational AI Concepts: Provide basic training on how tools like ChatGPT and Copilot work, their limits, and ethical considerations. Process Mapping and Redesign: Teach staff how to document and optimise workflows, focusing on approvals, handoffs, and exception management. Hands-on Tool Practice: Organise sessions where employees experiment with AI-generated outputs, such as automated reports or email drafting. Change Management Skills: Train on communication and stakeholder engagement to facilitate smooth transitions. Continuous Improvement Frameworks: Establish mechanisms for ongoing evaluation and refinement of automation outputs.Common Pitfalls to Avoid
It’s vital to sidestep common mistakes that undermine AI automation success:
- Tool-First Mentality: Avoid purchasing AI tools without understanding which workflows they will change and who will own those changes. Assuming All Staff Are Ready: Not everyone benefits equally from AI upskilling; selection matters. Lack of Clear Ownership: Projects without a designated lead often lose momentum or devolve into fragmented efforts. Ignoring Governance: Align automation projects with data protection and compliance policies. Overlooking Manual Tasks: Keep a running list of “tasks people still do by hand for no reason” and prioritise automating or improving them.
Conclusion
The automation revolution offers immense opportunities for SMEs, but success depends on far more than tools like smenews.digital ChatGPT or Copilot. Choosing the right employees to upskill—those with an automation mindset, process savvy, and leadership potential—is crucial. By asking "what changed in the workflow?" first, gaining clarity on roles and responsibilities, and designing thoughtful training, SMEs can accelerate sustainable AI automation that delivers real efficiency and growth.
As recognised by Southern Enterprise Awards 2026, companies that cultivate internal AI champions achieve better project outcomes and prepare their workforce for a future where human-AI collaboration is the norm.
Start your AI automation journey today by identifying your high-potential staff and involving them early. With the right approach, you’ll move beyond experimentation into scalable, impactful process transformation.