3 AI Lessons from 27 Data Leaders in 2025
What a year of conversations revealed about strategy, agents, and alignment
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2025 was supposed to be the year AI finally worked on its own. We were promised autonomous agents and decision-making without the inconvenience of pesky humans. But, after 27 conversations on the Data Faces podcast, the core message wasn’t about technology at all. It was about us.
In this day and age, it’s hard to get anyone to agree on anything. But after 27 conversations with thought leaders and practitioners, we did agree on one thing. It’s not the technology that is causing AI failures, well, mostly. What was clear was how broken our teams, alignment, and leadership already were. Having been through may of these cycles before, this isn’t new or novel.
“90% of Gen AI projects will fail to deliver transformative value. It’s not that the technology isn’t ready—most organizations aren’t.” — Kjell Carlsson, Domino Data Lab
This year, we talked to analysts, practitioners, and founders from Domino Data Lab, Dataiku, Ernst & Young, Monte Carlo, Relevance AI, Posit, BARC, and more. After 27 conversations, three patterns kept repeating.
Strategy before technology
The leaders who succeed don’t start with tools. They start with business outcomes. Not “let’s implement AI,” but “let’s solve this specific problem.” As Eric Kavanagh put it, the “ready-fire-aim” approach explains most of those failure rates.
“Leaders align AI outputs to corporate KPIs. That tethering of what the corporation wants to succeed with and what AI can help them do—that separates winners from laggards.” — Shawn Rogers, BARC
Agents need guardrails
Agentic AI is already here. It’s handling lead management, maintenance scheduling, and sales enablement. But governance is still a bit nascent. The companies that were doing it previously, such as financial services, healthcare, etc., are further ahead than most. It’s anticipated that some organizations may soon manage 10,000 or more agents. The companies getting this right aren’t moving faster. They’re treating agents like employees, with policies, oversight, and accountability.
“Wrap agents with employee-level policies. Ironically, agents may end up being more compliant than humans ever were.” — Sanjeev Mohan, SanjMo
The human element is the foundation
AI amplifies what’s already there. If your team isn’t aligned, your data isn’t trusted, or your messaging is generic, AI won’t fix it. It’ll expose it.
“If the team is not aligned beforehand, there’s no way whatever model you choose will be successful. Alignment is absolutely vital.” — Danny Stout, Ernst & Young
The same message came through in conversations about ethics, data quality, and messaging. Monica Cisneros pointed out that there are 21 mathematical definitions of fairness. Someone has to choose. Kevin Petrie was blunt. “If the quality ain’t good, the AI ain’t good.” And Emma Stratton warned of the curse of knowledge. Experts assume everyone understands what they do, then wonder why their messaging falls flat.
What 2025 actually taught us
The more powerful AI becomes, the more human skills matter. AI didn’t replace leadership, judgment, and clarity. It made the gaps impossible to ignore. That’s not a technology problem. That’s a mirror.
Hear the full conversations
This is the highlight reel. The full episode goes deeper. 27 guests on strategy, agents, ethics, and what’s coming in 2026.
27 leaders. 3 themes. 1 episode.
Listen to the Data Faces 2025 Year in Review.
🎧 YouTube | Spotify | Apple Podcasts
Listen to the full conversations on YouTube | Spotify | Apple Podcasts
Based on insights from 27 leaders featured on the Data Faces Podcast.
The Faces Behind Data: AI, Ethics, and Leadership with Monica Cisneros Data Faces Podcast with Monica Cisneros Nov 14, 2024 | Read more
Past as Prologue with Kevin Petrie: What History Tells Us About the Future of AI Dec 11, 2024 | Read more
AI in 2025: Why 90% of Gen AI Projects Will Fail | Kjell Carlsson Most AI failures aren’t about the technology—they’re about strategy, governance, and execution. Jan 2, 2025 | Read more
Solving the Data Trust Crisis with Kamal Maheshwari Kamal Maheshwari on solving the data trust crisis, aligning teams, and building AI-ready data ecosystems. Jan 21, 2025 | Read more
Beyond the AI Hype: What 20% of Companies Get Right Shawn Rogers breaks down BARC’s latest research on AI maturity, the importance of data quality, and what truly separates leaders from laggards. Feb 11, 2025 | Read more
AI Agents: State of the Union with Sanjeev Mohan Exploring the current state of AI agents, their challenges, and how businesses can prepare for widespread adoption. Feb 25, 2025 | Read more
The AI-Powered CFO: Why Finance Must Shift from Control to Cognition Jawwad Rasheed explains why AI, automation, and self-service analytics are transforming the role of finance leaders. Mar 11, 2025 | Read more
There Is No Post-AI World: Preparing Your Organization for the Agent Revolution John Thompson on the strategic value of AI agents, the unexpected risks of autonomous systems, and why intelligent governance matters more than ever. Mar 25, 2025 | Read more
The Gen AI Shift: How Product Marketing Managers Are Adapting Melissa Burroughs on scaling PMM productivity, balancing AI efficiency with messaging alignment, and preserving the human element in marketing. Apr 8, 2025 | Read more
The Grandmother Test: Building AI Trust Beyond Technology Robert Lake on asking the three essential business questions, managing the human tendency to anthropomorphize, and leading effective AI change management. Apr 22, 2025 | Read more
The Customer Hero Principle: Why Your B2B Messaging Falls Flat Gabriela Contreras on ruthless audience prioritization, escaping jargon land, and making customers the center of your product story. May 6, 2025 | Read more
Team Dynamics Over Technology: The Human Elements that Drive AI Success Danny Stout on human-centered AI teams, the myth of bigger models, and why communication skills trump technical prowess. May 20, 2025 | Read more
From “AI-Ready” to AI Reality: Why Actionable Data Strategies Beat Endless Planning Shane Murray on AI-ready data, the truth about RAG, and why building beats planning for trustworthy AI. Jun 3, 2025 | Read more
Stop Chasing Hallucinations—Focus on Agentic Quality Insights from Hyoun Park, CEO & Principal Analyst at Amalgam Insights, on fixing context gaps and building dependable AI agents. Jun 17, 2025 | Read more
The “Survival of the Nimblest” Strategy for AI Marketing Success Insights from Judit Szabo, Global Head of Demand Generation at Endava, on balancing automation with human connections in B2B marketing. Jul 1, 2025 | Read more
How AI Killed Traditional Competitive Analysis Insights from David Bryson, Principal Competitive Intelligence Manager at Splunk, on turning AI information overload into a strategic advantage. Jul 15, 2025 | Read more
How 3% of Companies Win with AI While 97% Fail Rich Mendis reveals the two misconceptions killing most enterprise AI projects and the proven framework that delivers ROI. Jul 29, 2025 | Read more
How to Write Punchy B2B Messaging That Actually Converts Emma Stratton from Punchy reveals the curse of knowledge killing most B2B conversions and the proven messaging framework that makes prospects say “yes.” Aug 12, 2025 | Read more
The AI Agent Mistake 90% of Marketing Leaders Are Making Chelsea Wise from Relevance AI reveals why learning together beats rushing to implement AI agents and the unsexy use cases that deliver real results. Aug 26, 2025 | Read more
Why Bad AI Governance Kills 95% of Enterprise Projects Before Production Thomas Been from Domino Data Lab explains why governance accelerates AI deployment by 70% and the validation trap that kills most enterprise projects. Sep 9, 2025 | Read more
Escape the Marketing Twilight Zone: The Agentic AI Playbook for B2B Marketers Rajeev Kozhikkattuthodi from Poexis reveals the three failure modes that prevent marketing teams from moving beyond analysis paralysis to measurable pipeline. Sep 23, 2025 | Read more
Your Netflix Moment: Why CIOs Must Act Now on AI Agents Catalina Herrera from Dataiku reveals why most AI agent pilots fail and the four-pillar framework that turns experimental projects into production systems. Oct 7, 2025 | Read more
Your AI Project Will Fail. Here Are the Only Three Decisions That Matter AI analyst and DMRadio host Eric Kavanagh on the three unglamorous decisions that separate AI success from expensive failure. Oct 21, 2025 | Read more
Augmented Intelligence: The Future of Sales Enablement LaunchDarkly’s Matt Magne shares why augmented intelligence beats automation in sales enablement. Nov 4, 2025 | Read more
The Barcode on the Bronze: Why Your AI Needs to Know What Makes You Different Adesso Associates’ Gina von Esmarch reveals how teaching AI your context beats generic automation. Nov 18, 2025 | Read more
Data Lineage for AI: Why Truth Beats Hope in Banking Insights from Tina Chace on ensuring data quality in AI deployments. Dec 2, 2025 | Read more
Why Code-First Data Science Still Wins in the Age of AI Posit’s Bruno Trimouille explains why governance and innovation aren’t a zero-sum game for data science teams. Dec 16, 2025 | Read more
About David Sweenor
David Sweenor is an expert in AI, generative AI, and product marketing. He brings this expertise to the forefront as the founder of TinyTechGuides and host of the Data Faces podcast. A recognized top 25 analytics thought leader and international speaker, David specializes in practical business applications of artificial intelligence and advanced analytics.
Books
Artificial Intelligence: An Executive Guide to Make AI Work for Your Business
Generative AI Business Applications: An Executive Guide with Real-Life Examples and Case Studies
The Generative AI Practitioner’s Guide: How to Apply LLM Patterns for Enterprise Applications
The CIO’s Guide to Adopting Generative AI: Five Keys to Success
Modern B2B Marketing: A Practitioner’s Guide to Marketing Excellence
The PMM’s Prompt Playbook: Mastering Generative AI for B2B Marketing Success
With over 25 years of hands-on experience implementing AI and analytics solutions, David has supported organizations including Alation, Alteryx, TIBCO, SAS, IBM, Dell, and Quest. His work spans marketing leadership, analytics implementation, and specialized expertise in AI, machine learning, data science, IoT, and business intelligence.
David holds several patents and consistently delivers insights that bridge technical capabilities with business value.
Follow David on Twitter@DavidSweenor and connect with him on LinkedIn.