• Understand AI’s Business Impact – Gain insights into how AI is reshaping industries and driving efficiency, growth, and profitability for SMEs.

• The AI Readiness Checklist – What SMEs need to prepare before implementing AI, including data readiness, management mindset, staff training and involvement, and infrastructure.

• For complex use cases: Understanding the data challenge – What kind of data is needed for AI, and how SMEs can work with limited data.

• Addressing change management and staff buy-in – How to align teams and ensure smooth AI adoption without resistance.

• AI Use Case Discovery Framework – Participants will use a structured framework (such as the AI Impact vs. Feasibility Matrix) to map their current business challenges to AI solutions.

• Personalized AI Opportunity Roadmap – Each participant will leave with a drafted 'AI Opportunity Playbook', outlining at least one AI use case they can explore in their business immediately.

• Decision-Making: Build vs. Buy AI – Attendees will work through a guided decision tree framework to determine whether to outsource AI solutions, adopt existing tools, or build in-house.

• Prototyping an AI Workflow – Using low-code/no-code AI tools, participants will mock up an AI-powered business process (e.g., automating customer inquiries, optimizing inventory, or streamlining operations).

• Scaling AI for Long-Term Business Growth – Learn how to evaluate AI ROI, what key metrics to track, and how to ensure AI investments align with business goals.

AI Readiness for SMEs – What’s Holding You Back?

What are your biggest concerns about AI adoption? Is it cost, talent, data, or something else? How have others tackled these challenges?

Starting Small: What’s the First AI-Powered Process You Can Automate?

What are some repetitive tasks in your business that AI could handle? What simple AI tools could you try immediately?

Building an AI-Ready Team: Who in Your Business Needs to Be Involved?

Does AI implementation require hiring? How can existing employees be upskilled for AI adoption? What internal resistance might you face?

Making Data Work for AI – How Much is Enough?

What data do you currently collect? How clean and structured is it? Can you start with minimal data, or do you need external sources?

AI & Finance: Smarter Decision-Making for Cash Flow & Forecasting

Can AI help with cash flow predictions, fraud detection, and financial reporting? What tools are SMEs using successfully?

Customer Experience 2.0 – Using AI for Better Engagement & Retention

How can AI personalize customer interactions? How have chatbots and AI-driven CRMs impacted businesses?

AI-Powered Marketing: Can AI Boost Your Sales?

What AI marketing tools exist today? How can AI help with lead generation, content creation, and ad targeting?

AI for Operations: How to Reduce Costs and Improve Efficiency

What are the top operational challenges AI could help with? How have other SMEs optimized supply chain, inventory, and workflows?

AI in HR: Can Automation Improve Hiring & Employee Retention?

What AI tools exist for talent acquisition, performance tracking, and employee engagement? Can AI help with SME workforce challenges?

Off-the-Shelf vs. Custom AI – Which is Right for Your Business?

Should SMEs develop their own AI or use existing tools? What factors influence this decision (cost, expertise, scalability)?

Choosing the Right AI Vendor – What to Look for in a Solution Provider

What key factors should SMEs consider when evaluating AI vendors? How do you avoid vendor lock-in and choose a scalable solution?

The Cost of AI: How to Budget for AI Adoption Without Overspending

What are the hidden costs of AI implementation? How can SMEs maximize ROI and avoid costly mistakes?

Measuring AI Success – What KPIs Matter for SMEs?

How do you track AI performance? What are the most important AI success metrics for different industries?

AI Ethics & Compliance – What SMEs Need to Know

How do data privacy laws affect AI adoption? What should SMEs be aware of regarding AI bias and responsible AI usage?

Scaling AI Beyond the First Use Case – What’s Next?

Once an AI solution is successful, how do you scale it across different business functions? What’s the best way to expand AI adoption?