AI That Actually Pays Off

🧭 The Just Curious Agency Symposium: A Hands-On AI Workshop

We’re planning a small-group virtual symposium for agency leaders who want to understand—not just imagine—how AI can create real business value.

Instead of panels or keynotes, you’ll join a select group of peers for hands-on working sessions led by 4–6 Just Curious AI experts. Each expert brings deep experience in applying AI to real agency challenges across operations, client management, finance, strategy, and creative.

Together, we’ll:

• Identify the use cases most likely to move the needle on revenue, margin, or client satisfaction

• Design practical solutions based on real-world implementations

• Leave with actionable strategies you can take back and apply immediately

Each session will go deep on:

• How AI is reshaping agency workflows and pricing models

• What smart, sustainable adoption looks like. Without the hype

• Where your agency can start right now (no matter your size or structure)

Want in?

Just reply with “Agency Symposium” and we’ll add you to the early invite list.

🎙 AI Expert of the Week: Ashley Gross

Founder, AI Workforce Alliance

From Endless Pilots to Real ROI: How to Get AI Right in Your Organization

Ashley Gross has helped businesses generate millions in revenue and radically accelerate execution by doing one thing exceptionally well: turning stalled AI efforts into real business outcomes.

In our conversation, she shared a field-tested playbook for SMB and enterprise leaders who want to stop experimenting and start winning.

🔥 Why Ashley’s Perspective Matters

If your team is stuck in AI pilot purgatory or struggling to show ROI, this one’s for you.
Ashley’s work is especially relevant for:

• GTM and marketing leaders trying to cut cycle times and unlock insight

• Strategy and transformation execs tired of expensive experiments

• AI PMs and consultants looking to increase adoption across the org

Her bottom-up meets top-down playbook blends automation, change management, and agentic design, without blowing up existing workflows.

📺 Watch & Learn

• Full Interview → From Endless Pilots to Real ROI

• 4-Min Case Study → From 90-Day Campaigns to 45 Minutes

• 45-sec Clip → The 30-Minute AI Litmus Test

🧠 5 Key Takeaways from Ashley

1. Define the business problem. Together.
   Start with one shared pain point—like slow sales cycles—and align cross-functional teams on solving it collaboratively.

2. Use a 30-minute test to kill zombie pilots.
   If you don’t see momentum in 30 minutes, something’s off. The tool, the framing, or the org isn't ready.

3. Automate what you repeat.
   “If I do it more than twice, I automate it.” This rule helped Ashley reduce campaign lead times from 90 days to 45 minutes.

4. Meet teams where they already work.
   Ashley builds agentic interfaces that look like a teammate in Microsoft Teams, because the best AI adoption happens invisibly.

5. Build in emotional intelligence.
   AI transformation is emotional, not just technical. Ashley never changes a workflow unless absolutely necessary, and adoption skyrockets as a result.

🎥 From the Vault: Favorite Interviews You May Have Missed

We’ve been publishing a lot, so here’s a curated batch of interviews chosen specifically for their clear, practical insights into strategy, marketing, and enterprise adoption of AI.

Each one breaks down how AI is being deployed right now: in marketing, product development, strategic planning, and enterprise workflows.

This week’s experts:

• Mike Mayes (ex-BCG) on building a business case

• Andreas Sjöström (Capgemini) on deploying agents

• Aanikh Kler (Laser) on startup-to-enterprise implementation

• Matt Seitz (former Google exec) on marketing ROI

🧠 Why Your AI Strategy Needs a Business Case

Mike Mayes, Founder of Egoless Consulting & Former BCG Partner

 Watch the full interview →

Mike warns against “AI as a hammer” thinking, advocating instead for strategy-first alignment. He shares frameworks and a standout case study from a reinsurance firm that mapped 10,000 contracts with GenAI.

Key Takeaways:

• Lead with business value, not tech excitement. AI should support existing strategic priorities, not create new distractions.

• Map the value chain. Identify high-cost or high-value workflows, then prioritize AI investments accordingly.

• Don't delegate AI strategy to the CTO. Business unit leaders should define the problem; tech teams should build the solution.

• Jobs to be done > status quo workflows. Use AI to redesign roles and rethink how work gets done, don’t just speed up old habits.

• Involve frontline teams early. You'll get better adoption and better ideas by engaging the people closest to the work.

🛠 From AI Hype to Real Results: How Startups Scale Successfully

Aanikh Kler, General Manager at Laser Technologies

 Watch the full interview →

Aanikh walks through what it really takes to implement AI in startup and enterprise environments, cutting through hype with real frameworks, examples, and lessons from clients like VC firms and health tech platforms.

Key Takeaways:

• Start small, solve real problems. Overbuilding V1s leads to disappointment. Get early wins, then iterate.

• Data prep is make or break. You need structured, validated data mapped to real use cases. No shortcuts.

• Think workflows, not widgets. The most successful projects embed AI invisibly inside existing team tools (e.g., Microsoft Teams).

• Internal tools create early ROI. Especially in regulated industries like health or finance, behind-the-scenes automation is often the best first step.

• Use AI to free up humans. From campaign planning to investment research, the biggest win is reclaiming time for high-leverage work.
  

📊 Stop Guessing, Start Measuring: How AI Proves Marketing ROI

Matt Seitz, Director of the AI Hub at UW & Former Google Executive

 Watch the full interview →

Matt draws on decades of experience with Fortune 500 brands to unpack how marketing leaders can use AI to drive measurable outcomes, without losing brand integrity or customer insight.

Key Takeaways:

• Use AI where it’s better—and let go. Automate tactical decisions, but keep humans focused on high-value creative and strategic work.

• Build a balanced scorecard. Avoid AI over-optimization by aligning on shared business metrics across teams.

• Move from ROAS to business impact. AI that optimizes for short-term performance can hurt long-term brand value.

• Run fast experiments. High-velocity testing helps teams evaluate tools, improve results, and build AI fluency faster.

• Educate and engage. Marketers who learn the tools become strategic drivers—not victims—of transformation.
  

🤖 How AI Agents Transform Enterprises

Andreas Sjöström, VP at Capgemini Applied Innovation Exchange

Watch the full interview →

Andreas shares what he’s learned from engaging with 400+ agentic AI startups, and helping enterprises deploy agents across functions from supply chain to the C-suite.

Key Takeaways:

• AI agents are already reshaping how work gets done. From boardroom strategy assistants to autonomous developer tools, agents are becoming integral to enterprise workflows.

• Balance top-down and bottom-up experimentation. Strategic planning and hands-on piloting must happen in parallel.

• Start with high-value, low-complexity wins. Use a value/complexity matrix to identify fast paths to ROI.

• Data quality is the biggest blocker. Even the best agents fail without solid, structured, domain-specific data.

Empower experimentation. Encourage teams to build, test, and share learnings. Curiosity is a competitive advantage.

🔍 My Favorite Things Last Week

Here are two podcasts I enjoyed last week that complement the actionable lessons above—both offering insights on strategic clarity, sustainable advantage, and effective AI investment:

• Michael Dell - Founders Podcast: How Michael Dell used strategic clarity, cost efficiency, and bold decisions to transform Dell, and what it teaches leaders investing in AI-driven growth and innovation.

• Sir Chris Hohn - In Good Company: How the legendary investor identifies durable competitive advantages, and what leaders can learn about using AI to build lasting profitability and defensibility.

Michael Dell - Founders Podcast

Michael Dell's journey offers profound insights for business leaders aiming to transform their organizations through AI. His principles, though rooted in the tech hardware industry, are universally applicable to strategic decision-making and innovation.

👉 Check out the episode →

🧠 Key Lessons for AI-Driven Business Transformation (Inspired by Michael Dell)

1. Leverage Cost Efficiency as a Strategic Advantage: Dell's success was partly due to maintaining lower operating costs than competitors, allowing for competitive pricing and reinvestment in innovation. Similarly, AI can be utilized to streamline operations, reduce expenses, and allocate resources more effectively.

2. Maintain Deep Understanding of Your Business: Dell emphasized knowing every aspect of his company. For AI integration, leaders should thoroughly understand their processes to identify where AI can add the most value and ensure its effective implementation.

3. Commit to Long-Term Vision Over Short-Term Gains: Dell's decision to take his company private and invest in long-term growth, including AI capabilities, highlights the importance of patience and strategic planning in transformation efforts.

4. Embrace Bold Moves When Necessary: Dell's acquisition of EMC was a significant risk that positioned the company for future success. Similarly, businesses should be prepared to make substantial investments in AI when aligned with their strategic objectives.

5. Integrate AI into Core Business Functions: Rather than treating AI as an add-on, Dell's approach suggests embedding new technologies into the core operations of the business to drive meaningful change and value creation.

🎯 Recommended Actions for SMB Leaders

• Conduct a Comprehensive Audit: Evaluate current processes to identify areas where AI can enhance efficiency and effectiveness.

• Develop a Clear AI Strategy: Align AI initiatives with the company's long-term goals and ensure they are integrated into the broader business strategy.

• Invest in Talent and Training: Equip teams with the necessary skills and knowledge to work alongside AI technologies effectively.

• Monitor and Measure Impact: Establish metrics to assess the performance of AI initiatives and make data-driven decisions for continuous improvement.

• Stay Agile and Open to Change: Be prepared to adapt strategies as AI technologies evolve and new opportunities emerge.

👉 Check out the episode →

AI investments, like great financial investments, require long-term thinking, defensible competitive advantages, and a relentless focus on essential, recurring customer needs. Chris Hohn’s investment philosophy—emphasizing durability, defensibility, profitability, and deep integration—translates powerfully into strategic guidance for SMB and enterprise leaders considering how to strategically deploy AI

👉 Check out the episode →

🧠 Key Lessons for Leaders Transforming Their Businesses with AI (Inspired by Chris Hohn)

1. Invest in AI where you have strong internal "moats." Just as investors seek durable competitive advantages, businesses should focus AI on processes, products, or workflows where they already have unique strengths, like proprietary data, deep domain expertise, or complex workflows. These become internal moats that make AI integration especially powerful and difficult to replicate by competitors.

2. Solve problems that matter. Focus on essential needs. Prioritize AI projects that directly impact critical business functions (sales, client retention, cost reduction). Avoid spending resources on discretionary or superficial "AI experiments" without clear business outcomes.

3. Think profitability first, not novelty. Deploy AI strategically to significantly reduce costs, automate low-value processes, and enhance pricing power. The best AI use-cases aren’t the flashiest; they're the ones that measurably boost profit margins or free up your highest-value talent for more strategic tasks.

4. High switching costs drive adoption and lasting value. Design your AI solutions to integrate deeply and seamlessly into existing team workflows. Solutions that feel like natural extensions of existing processes (rather than disruptive new tools) lead to greater user adoption and sustainable competitive advantage.

5. Long-term thinking outperforms quick wins. AI transformation isn’t about immediate results; it’s about sustained, compounding improvements. Consider your AI initiatives as long-term strategic investments. Think 3–5 years, not just 3–6 months.

6. Pricing power = validation of your AI solution’s value. If your AI-driven enhancements are truly valuable, customers will recognize and pay for that value. Internally, this translates into solutions that stakeholders value highly and rely on deeply, further embedding them into your core operations.

🎯 Recommended Actions for Leaders Using AI to Transform Their Businesses

• Audit your internal "moats." Identify what makes your business uniquely effective or valuable, then prioritize AI applications that reinforce or extend those strengths.

• Focus on “jobs to be done.” Start with your team's real problems, those tasks that directly generate revenue, retain customers, or create value. Build AI solutions to streamline or automate those jobs.

• Measure impact via profitability, not just productivity. Judge AI initiatives by their effect on profitability: Does your AI effort meaningfully lower costs, increase sales effectiveness, or raise customer lifetime value?

• Build AI solutions into existing workflow “bundles.” Just like Microsoft bundled Teams, integrate AI into tools and processes your teams already love and use daily. Avoid forcing new workflows; make it easy to adopt and hard to leave.

• Play the long game / Think like a strategic investor. Don’t chase every shiny AI tool. Pick 1–3 strategically aligned projects, fund them consistently, and commit to measuring and iterating on them for the long term.

👉 Check out the episode →