on-demand

From AI Pilot to ROI: How Growing Businesses Use AI Work

  • Understand why most AI initiatives fail to show measurable ROI
  • Learn a four-layer framework to evaluate AI from model performance to business outcomes
  • Identify the hidden data, workflow, and adoption gaps that quietly limit returns
  • Apply a phased approach to improve AI performance and justify further investment
AVAILABLE ON DEMAND
1 hour

Here is how to turn AI pilots into measurable business results.

You have made the AI bet. A chatbot in customer service, automation in finance, or a forecasting model in operations. The pilots showed promise. The investment kept growing.

But one question remains: why are these AI initiatives not translating into measurable business results?

According to McKinsey & Company, 78% of organizations now use AI in at least one business function, yet only a small share report significant financial impact.

The issue isn’t adoption. The issue is not adoption. It is the gap between successful pilots and real-world ROI. 

Most teams lack a structured way to assess where AI is working, where it’s breaking down, and whether the use case was a fit to begin with. In many cases, AI systems appear to perform well in controlled environments but fail to deliver consistent value in real workflows.

Without a structured way to evaluate AI beyond surface-level metrics, it becomes difficult to separate meaningful outcomes from activity. This is where most AI efforts stall: the transition from pilot success to operational impact.

This webinar gives you a practical AI evaluation framework to assess performance across models, outputs, workflows, and business outcomes. You will learn how to identify where value is being lost and what needs to change to improve AI ROI.

What you’ll take away

In this session, you’ll learn how to move from AI pilots to measurable ROI through:

  • A clear framework to move AI initiatives from pilot stage to measurable business outcomes without scaling inefficiencies.
  • Four-layer AI evaluation framework for assessing any AI initiative, from model accuracy to business outcome, with the diagnostic questions to ask at each layer.
  • Method for matching AI to the right processes, so you can tell which use cases are well-suited for AI, which aren’t, and what realistic expectations look like for each.
  • Practical approach to measuring AI performance, including how to baseline before deployment and how to phase investment so each phase informs the next.
  • A clear view of why most mid-market AI programs stall, and the foundation issues that limit AI ROI across departments.
  • A practical improvement loop for fixing AI initiatives that aren’t yet delivering, instead of writing them off.

There will be a live Q&A session where you can bring your hardest AI evaluation questions for our experts.

Who should attend?

CEOs, CIOs and CTOs IT Directors and VPs of Operations Digital Transformation leaders

Speakers

personyasir rizwan

Yasir Rizwan

CTO

Yasir Rizwan, EVP & CTO at tkxel, brings over 27 years in tech, driving IT transformation and hyper-growth initiatives. Also the Founder of Techfoot, Yasir is recognized for leadership excellence and industry impact.

persondr shahzad cheema

Dr. Shahzad Cheema

CAIO

Dr. Shahzad Cheema is an AI strategist and coach with deep expertise in artificial intelligence and technology leadership. He has spent over two decades working on AI applications and shaping how organisations understand and adopt intelligent systems.

Frequently Asked Questions (FAQs)

What does it mean to move from AI pilot to ROI?
Moving from AI pilot to ROI means transitioning from isolated experiments or proof-of-concepts to real business impact. This involves integrating AI into workflows, aligning it with business goals, and measuring outcomes such as cost reduction, efficiency, or revenue improvement.
Why do most AI initiatives fail to show ROI?
Most AI initiatives fail to show ROI because organizations measure model accuracy but not business outcomes. According to McKinsey, 78% of companies use AI but few report significant financial impact. The gap is rarely the technology itself. It is the absence of a structured way to evaluate where value is being lost across the model, the workflow, and the broader business process.
How do you evaluate AI performance and ROI?
You evaluate AI performance by assessing four connected layers: model accuracy, output quality, workflow integration, and business outcome. Measuring only one layer, such as model accuracy, gives an incomplete picture. A structured evaluation framework helps identify exactly where AI value is being lost and what to fix.
Who should attend this webinar?
This session is designed for business and technology leaders responsible for AI strategy, investment, or execution. It is especially relevant for mid-market organizations looking to move beyond pilots and deliver measurable AI outcomes.
What will I learn from this webinar?
You will learn how to evaluate AI across models, outputs, workflows, and business outcomes, identify where value is being lost, and apply a structured approach to improve AI performance and ROI.
Do I need a mature AI setup to benefit from this session?
No. Whether you are early in your AI journey or working to improve existing initiatives, this session provides a practical AI evaluation framework that applies at different stages of adoption.
How is this different from other AI webinars?
Most AI webinars focus on tools, trends, or use cases. This webinar focuses on AI evaluation and performance, helping you understand what is actually working and how to improve it.
Will there be an opportunity to ask questions?
Yes. There will be a live Q&A session where you can bring your specific AI evaluation challenges and get direct input from the speakers.
How will this help me apply AI in my business?
You will leave with a clear AI evaluation framework to assess your current initiatives, identify high-impact opportunities, and take practical steps to improve results in real workflows.

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