EP 271 - How to Quantify AI ROI Beyond ‘Time Saved’
Release Date: 12/25/2025
EP 274 The Human OS - AI Adoption With Curiosity, Safety, and Monday Ease ft. Melissa Penton
AI Literacy for Entrepreneurs
In the final episode of the Podcast-to-Book series, host sits down with change leader and AI education lead (Sun Life) for a human-first conversation about what actually makes AI adoption work. They talk productivity vs room-for-life, why one-prompt culture is snake oil, the shift from prompt engineering to context engineering, and the simplest enterprise question that changes everything: “What would make Monday easier for employees?” Episode summary Susan closes out the Podcast-to-Book sprint with a conversation that feels like the point of the whole series: AI isn’t a tool problem....
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273 - Future-proofing your organization through continuing AI literacy
AI Literacy for Entrepreneurs
Most companies do a few AI trainings, run some pilots, and then stall. In this episode, host argues the only real future-proofing strategy is continuous AI literacy. She breaks down what “continuous literacy” actually includes (skill, judgment, workflow, norms), the predictable failure modes of the AI literacy divide, and a simple flywheel you can run monthly so capability keeps compounding. Episode summary Susan opens with a familiar pattern: a burst of AI excitement, a deck called “AI Strategy 2025” a few clever workflows… and then reality hits. Tools change. Policies shift....
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EP 272 - Mindset, Sales, and AI That Actually Helps with Gazzy Amin
AI Literacy for Entrepreneurs
Host sits down with sales strategist , founder of Sales Beyond Scripts, to talk about the real ways AI is changing revenue, planning, and scale. They cover AI as a thinking partner, how to use it across departments in a small business, why audits matter more than hype, and how mindset quietly determines whether you treat AI as a threat or an advantage. Episode summary This episode is part of Susan’s 30-episodes-in-30-days “podcast to book” sprint for Swan Dive Backwards. Susan and Gazzy zoom in on the selling process first. Then they zoom out to the whole business. They talk about three...
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EP 271 - How to Quantify AI ROI Beyond ‘Time Saved’
AI Literacy for Entrepreneurs
If you’re measuring AI success by “hours saved” you’re playing the easiest game in the room. In this episode, Host explains why time saved is weak and sometimes harmful, then shares a better “AI ROI stack” with five metrics that map to real business value and help you build dashboards that actually persuade leadership. Episode summary Time saved is fine. It’s also table stakes. Susan breaks down why “we saved 200 hours” is the least persuasive AI metric, and why it can backfire by punishing your early adopters with more work. She then introduces a smarter approach: a...
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EP 270 - From AI Awareness → AI Readiness → AI Adoption with Jennifer Hufnagel
AI Literacy for Entrepreneurs
Host sits down with (Hufnagel Consulting), an AI educator and AI readiness consultant who’s trained 4K+ people. They break down what “AI readiness” actually means (spoiler: it’s not buying Copilot), why AI doesn’t fix broken processes or dirty data, and how leaders can build real capability through training programs, communities of practice, and properly resourced AI champions. Episode summary and met in “the most elite way possible”: both were quoted in The Globe and Mail about women and AI. Jennifer shares her background as a business analyst and digital adoption / L&D...
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EP 269 - Why One-Off AI Training Fails (and What to Do Instead)
AI Literacy for Entrepreneurs
If your organization ran an “AI 101” lunch-and-learn… and nothing changed after, this episode is for you. Host explains why one-off workshops create false confidence, how AI literacy is more like learning a language than learning software buttons, and shares a practical roadmap to build sustainable AI capability. Episode summary This episode is for two groups: teams who did a single AI training and still feel behind, and leaders realizing one workshop won’t build organizational capability. The core idea is simple: AI adoption isn’t a “feature learning” problem. It’s a...
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EP 268 Women, AI, and ‘Hold the Door’ Leadership with Chris McMartin
AI Literacy for Entrepreneurs
Host is joined by , National Lead for the Scotiabank Women Initiative (Business Banking), for a real-world conversation about how women are approaching AI. They talk about time poverty, fear of asking “dumb” questions, the shame myth of “AI is cheating”, and why the most powerful move right now is women holding the door open for each other - learning in community and sharing what works. Episode summary This episode is a candid, energetic conversation with Chris McMartin - aka “Hype Boss” online and a long-time hype woman for women entrepreneurs. They explore what’s different...
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EP 267 Does AI Make you More or Less Creative? (Paintbrush vs Photocopier)
AI Literacy for Entrepreneurs
AI can feel like a creativity cheat code… or like the death of originality. In this short, punchy solo episode, Susan argues the truth is simpler: AI doesn’t create creativity. It creates options. Creativity still belongs to the driver—your taste, courage, and point of view. Episode summary Susan tackles a question she hears constantly: does AI expand creativity or flatten it? Her answer: it depends on how you’re using it. If you use AI like a photocopier—generate a first draft and ship it unchanged—you’re not becoming more creative. You’re becoming more efficient at being...
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EP 266 - Literacy, Leadership, and the ‘AI for the Sake of AI’ Trap with Shona Boyd
AI Literacy for Entrepreneurs
Host is joined by , a product manager at Mitratech, a SaaS company, and a proudly AI-curious early adopter, for a grounded conversation about what AI literacy actually means now. They talk about representation, critical thinking, everyday meet-you-where-you-are workflows, shadow AI, enterprise guardrails, and why leaders must stop chasing AI features that don’t solve real user problems. Episode summary Susan introduces Shona Boyd - AI-curious early adopter and SaaS product manager—whose mission is to make AI feel less scary and more accessible. Shona shares how her approachable AI...
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265 Buying AI vs Building AI - A Leader’s Decision Guide
AI Literacy for Entrepreneurs
Most teams are stuck in tool obsession: “Should we build agents?” “Should we buy this AI platform?” In this solo, workshop-style episode, host pulls you back to reality with a simple decision guide: buy vs bolt-on vs build, four leadership filters, and a practical workflow exercise to help you choose the right approach - without falling for agentic fantasies. Episode summary Susan opens with a pattern she’s seeing everywhere: 75% of AI conversations revolve around tools - agents, platforms, add-ons - and they’re often framed as all-or-nothing decisions. She reframes it: AI is best...
info_outlineIf you’re measuring AI success by “hours saved” you’re playing the easiest game in the room. In this episode, Host Susan Diaz explains why time saved is weak and sometimes harmful, then shares a better “AI ROI stack” with five metrics that map to real business value and help you build dashboards that actually persuade leadership.
Episode summary
Time saved is fine.
It’s also table stakes.
Susan breaks down why “we saved 200 hours” is the least persuasive AI metric, and why it can backfire by punishing your early adopters with more work. She then introduces a smarter approach: a set of five metrics that connect AI usage to quality, risk, growth, decision-making, and compounding capability.
If you want your AI work funded, supported, and taken seriously, you need to move the conversation from cost to investment. This episode shows you how.
Key takeaways
Time saved doesn’t automatically convert to value.
If no one reinvests the saved time, you just made busy work faster.
Hours saved can punish high performers.
Early adopters save time first.
They often get “rewarded” with more work.
Time saved misses the second-order benefits.
AI’s biggest wins often show up as fewer mistakes, better decisions, faster learning, and faster response to opportunity.
Susan’s “AI ROI stack” has five stronger metrics:
-
Quality lift
Is the output better?
Track error rate, revision cycles, internal stakeholder satisfaction, customer satisfaction, and fewer rounds of revisions (e.g., proposals going from four rounds to two). -
Risk reduction
AI can reduce risk, not only create it.
Track compliance exceptions, security incidents tied to content/data handling, legal escalations/load, and “near misses” caught before becoming problems. -
Speed to opportunity
Measure time from idea → first draft → customer touch.
Track sales cycle speed, launch time, time to assemble POV/brief/competitive responses, and responsiveness to RFPs (the “game-changing” kind of speed). -
Decision velocity
AI can reduce drag by improving clarity.
Track time-to-decision in recurring meetings, stuck work/aging reports, decisions per cycle, and decision confidence. -
Learning velocity
This is the compounding one.
Track adoption curves, playbooks/workflows created per month, time from new capability introduced → used in production, and how many documented workflows are adopted by 10+ people.
Dashboards should show three layers:
Leading indicators (adoption, workflow usage, learning velocity).
Operational indicators (cycle time).
Business outcomes (pipeline influence, time to market, cost of service).
You’re not investing in AI to save hours.
You’re building a system that produces better work, faster, with lower risk, and gets smarter every month.
Timestamps
00:01 — “If you’re measuring AI success by hours saved… that’s table stakes.”
00:51 — Why time saved doesn’t translate cleanly into value
01:12 — Time saved doesn’t become value unless reinvested
01:29 — Hours saved can punish high performers (they get more work)
02:10 — Time saved misses second-order benefits (mistakes, decisions, learning)
02:45 — Introducing the “AI ROI stack” (five better metrics)
02:59 — Metric 1: Quality lift (error rate, revision cycles, satisfaction)
03:31 — Example: proposal revisions drop from four rounds to two
04:14 — Metric 2: Risk reduction (compliance, incidents, legal load, near misses)
05:19 — Metric 3: Speed to opportunity (idea to customer touch, sales cycle, launches)
06:11 — Example: RFP response in 24 hours vs five days
06:34 — Metric 4: Decision velocity (time to decision, stuck work, confidence)
07:30 — Metric 5: Learning velocity (adoption curve, workflows, time to production)
08:57 — Dashboards: leading indicators vs lagging indicators
09:15 — Dashboards should include business outcomes (pipeline, time to market, cost)
09:32 — Reframe: AI as a system that improves monthly
10:08 — “Time saved is the doorway. Quality/risk/speed/decisions/learning is the house.”
10:36 — Closing + review request
If your AI dashboard is only “hours saved” keep it - but don’t stop there.
Add one metric from the ROI stack this month.
Start with quality lift or speed to opportunity.
Then watch how fast the conversation shifts from cost to investment.
Connect with Susan Diaz on LinkedIn to get a conversation started.
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