If you've invested in AI and you're wondering why your P&L isn't showing the gains you expected, this episode is for you.
Svetlana Makarova, AI strategist who scaled solutions at Mayo Clinic, breaks down the biggest paradox in enterprise AI: Why 90% of companies report AI adoption while 95% see NO measurable P&L impact.
She reveals the truth about MIT vs. Wharton reports, introduces you to Solow's Paradox (history repeating from the PC revolution), and explains exactly what you need to do differently to see real returns.
⏱️ KEY TIMESTAMPS:
00:00 - The ROI Question: AI adoption is soaring, but what about P&L?
00:56 - Wharton Report: 90% adoption, everyone's happy
01:24 - MIT Report: 95% of AI projects show NO measurable P&L impact
01:33 - Why these reports contradict each other
01:42 - What Wharton was measuring vs. MIT
01:55 - The Copilot/Gemini/ChatGPT adoption wave
02:09 - Companies seeing ROI: Tech-first firms like Netflix, Google, Meta
02:42 - Why custom solutions built on proprietary data win
03:02 - Productivity isn't always measured in P&L
03:11 - Employee satisfaction, time back, alleviating burnout
03:16 - Healthcare-specific: Burnout reduction as ROI
03:54 - To see impact: Build customized solutions with YOUR data
04:08 - Reality check: Takes years for change management
04:25 - Current state: Led by out-of-the-box tools
04:40 - Most AI projects avoid business-critical operations
06:00 - Introduction to Solow's Paradox
06:26 - PC Revolution: Companies invested heavily, saw no productivity gains
06:57 - "Where the heck are these productivity gains we were promised?"
07:10 - Recommended reading on Solow's Paradox
07:32 - The measurement problem: How you quantify determines what you see
07:45 - Organizations had to develop new metrics for computer ROI
08:01 - Out-of-the-box tools: Feeling productivity, becoming happier
08:28 - Critical insight: Unless you redesign workflows, don't expect change
08:47 - How to quantify: Tasks completed, time reduction
09:00 - Reengineering workflows and reassigning roles
09:13 - "If you're continuing to do things as you used to, how can you expect metrics to change?"
09:27 - Introducing AI alone doesn't translate to ROI
09:37 - Revenue ROI: Mission-critical systems, customer service, AI agents
10:02 - Attribution and goal-setting for AI agents
10:13 - Third bucket: Human value and workforce satisfaction
10:25 - Healthcare revenue is driven by workers who can't be automated
10:41 - Objective: Keep everyone healthy, happy, not overworked
10:55 - Service industries: Maintaining human-to-human relationships
11:09 - Soft metrics that deliver ROI but are hard to quantify
🎙️ About the Guest:
Svetlana Makarova is an AI strategist with nearly 5 years of experience building AI solutions in highly regulated healthcare environments, including Mayo Clinic. She's currently pursuing a doctorate in Applied AI/ML and advises companies across sectors on AI adoption strategy. Upcoming TEDx speaker on AI.
🔗 CONNECT WITH SVETLANA:
LinkedIn: https://www.linkedin.com/in/svetlanamakarova/
📧 Connect with Host
Host Deepti Kalghatgi : https://www.linkedin.com/in/deepti-kalghatgi/
🌐 Visit: https://idaahub.com
How are you measuring AI ROI in your organization? Are you tracking P&L, productivity, or human value metrics? Share your experience in the comments!
#AIAdoption #ROI #DigitalTransformation #AIStrategy #Productivity #ChangeManagement #HealthcareAI #EnterpriseTech #AIMetrics #BusinessTransformation #SolowsParadox #HealthTech #AIinHealthcare
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