The Hathaway Enterprise Value Framework

How I Approach Building Plans That Drive Commercial Value

I get some version of this question in almost every conversation about a new opportunity: how would you approach this? This is my answer — the framework I use when building a plan to drive commercial and enterprise value, independent of industry, company size, or which function I happen to be sitting in at the time.

I’ve been fortunate to be surrounded by very accomplished mentors who have shaped my business acumen. I did not come up with this on my own; it’s the result of putting methodology and frameworks into real-world practice from those who have actually done it. It’s based on decades of real-world application from those with deep expertise in value creation (I also have first hand experience in value destruction and there’s many lessons from that too). I collaborate deeply in my pursuit of continual growth and enjoy shaping the next generation of leaders in similar ways.

The Executive Premise

Most organizations pursue growth by optimizing individual functions — marketing, sales, technology, operations — independently. That work often improves local performance, but it rarely changes enterprise value in a durable way.


I start from a different premise: enterprise value is created by the interaction of capabilities across an organization, not by any single function working in isolation. In a complex matrix organization, that value depends on skilled collaboration across functions as much as it depends on any one function’s execution — and seeing that requires the ability to work across boundaries, not necessarily sitting at the top of any specific one of them. My focus is identifying where capability is constrained, where value is leaking between functions, and where investment will create durable competitive advantage rather than only short-term lift.

Seven Principles That Guide the Work

1. Enterprise Value First Not every plan needs to answer the same questions. Long-range, enterprise-level plans have to answer three: Does it create enterprise value? Does it reduce strategic risk? Does it strengthen long-term organizational capability? Quarterly functional plans — a stronger campaign, a faster process, a tighter funnel — are judged on a different, more immediate bar: are they moving the business forward this quarter? Both are necessary for sustainable growth. The discipline is knowing which lens applies to which plan, and making sure the near-term wins are building toward the enterprise questions rather than running in a separate lane from them.

2. Observe Before Prescribing Initial conversations should produce observations and hypotheses, not definitive recommendations on day one. A disciplined assessment validates assumptions before capital gets committed — moving fast on the wrong hypothesis is more expensive than moving deliberately on the right one.

3. Capability Before Strategy Most organizations already know what they want to achieve. What determines whether that strategy becomes reality is operating capability — leadership, governance, talent, technology, decision-making, and data quality. I look at capability first, because strategy without it is just a wish list.

4. Knowledge as an Enterprise Asset Institutional knowledge is an enterprise asset, not a byproduct of individual tenure. Structured documentation, decision intelligence, and thoughtful use of AI can preserve organizational memory, accelerate onboarding, improve succession planning, reduce dependence on any one executive, and strengthen resilience through change.

5. Commercial Capability as One System Marketing, sales, customer experience, partnerships, and service create more value when they’re treated as one commercial system rather than isolated departmental goals competing for the same budget and the same customer’s attention. That alignment doesn’t necessarily require one person owning all functions — it requires someone willing to work the seams between them, translate priorities across boundaries, and keep the whole system pointed at the same outcome.

6. Digital Infrastructure in Service of Decisions I evaluate technology investments by their ability to improve decision quality, customer experience, organizational learning, and well-defined workflow execution — not simply by the automation or efficiency gains they promise. A tool that makes an organization faster at the wrong thing isn’t progress.

7. Strategic Optionality Healthy organizations retain the ability to scale, integrate acquisitions, withstand leadership transitions, attract capital, and adapt to changing markets. I weight recommendations toward preserving and expanding that flexibility.

How This Plays Out: A Five-Stage Sequence

This is the sequence I follow — a disciplined progression, not a predetermined set of answers delivered on day one.

  1. Observe. Understand the enterprise context before forming a point of view.
  2. Assess. Structure that observation into a clear-eyed view of capability and constraint.
  3. Validate. Test hypotheses against real data before committing capital or organizational energy.
  4. Design. Build the blueprint once the hypothesis holds up.
  5. Enable. Put the capability, governance, and change management in place to make the design real.

What This Looks Like in Practice

In practice, this rarely starts with a finished plan. It starts with a small, concrete illustration — often built from nothing more than public information and a handful of early conversations — that shows how I’d think about a specific problem, not a claim that I’ve already solved it.

That first pass usually reflects Principles 1 and 5 most visibly: it starts from observed dynamics rather than a predetermined tactic list, and it treats the functions involved as one connected system rather than separate initiatives competing for attention. The next step is always the same regardless of the situation: validate those early observations against the organization’s actual data before treating any of them as settled. That’s an invitation for the team’s input, not a claim that the first draft is already right.

The Questions I Bring to the Table

These are the questions I keep in view across every conversation, regardless of which function we’re discussing in the moment:

  • Where is enterprise value being created today?
  • Where is value leaking because capabilities are fragmented?
  • What knowledge leaves the organization when a key leader departs?
  • What capabilities need to exist three years from now that don’t exist today?
  • What investments create enduring value, rather than short-term performance?

This is the lens I bring to every plan I build. If you’re working through a similar question — how to unlock enterprise value across a complex organization — I’d welcome the conversation.

— Jourdan Hathaway

DRIVEN: my operating model for leadership

I bring a track record of outcomes that reflect what I like to think of as a “Swiss Army knife” business leader. I’ve led some defining chapters—scaling a business 4x, improving EBITDA by ~30% year over year, and driving a full turnaround to breakeven.

I’ve served as Chief Marketing Officer, Chief Operating Officer, and Chief Business Officer—roles that require not just functional expertise, but strong business acumen, high EQ, and a real ability to connect with people and lead through complexity.

I’m also an AI-enabled operator who leads hybrid teams with agentic AI agents embedded in various departments. I know how to use AI to increase speed, scale, and operational efficiency, but I also know when human discernment, judgment, and inspiration are what matter most. I lead by knowing the difference.

Over the years, I’ve come to understand that leadership isn’t just about strategy, operations, or metrics. Those are table stakes. The real differentiator is how you show up as a human being.

For me, that’s captured in an acronym: DRIVEN.

D – Determined: I will find a way. From shopping carts to boardrooms, determination has been the throughline.
R – Resilient: The path has never been linear. Doors close. Plans fall apart. I keep going.
I – Impactful: If I’m in a role, a room, or a relationship, I’m there to move something meaningful forward—for the business and for people.
V – Vulnerable: I say “I don’t know” when I don’t. I ask for directions from those who’ve been where I want to go.
E – Empathetic: I’ve lived what it means to start from “less.” That shapes how I hire, how I coach, and how I design opportunity.
N – Nimble: I’m willing to reinvent myself, to pivot, to learn in public when the world or the business demands it.

The “V” and the “E” have been the hardest-won and most transformative for me. Vulnerability and empathy aren’t soft skills; they’re force multipliers. They’re how trust gets built. They’re how cultures of continuous learning actually take root.

This combination for me is about having an achievement mindset and a bias for growth and action while also being profoundly self-reflective and tuned-in to others around me.

‘DRIVEN’ – Determined. Resilient. Impactful. Vulnerable. Empathetic. Nimble.

I can’t “arrive” somewhere I don’t know how to get to. So I routinely seek out people who have the map, whether it’s a CFO walking me through a new financial construct, a seasoned operator helping me see around corners, or a speaker helping me refine a keynote.

And every time I find my way to that new place, I turn around and offer the directions to others.

That’s what leadership is to me: not a title, but a practice of turning your hard-won maps into pathways for other people.

Yes, That’s a Hairbrush. This Is How It Started. What My Early Public Speaking Practice Actually Looked Like.

Is that a hairbrush as a microphone? Yup. Are there notecards taped to the wall? Also yup.

This is a behind-the-scenes look at how my public speaking practice started back in the day. I reject the idea that just because I’m an executive, I should only share the polished veneer that “looks the part.” It’s not real. It’s not how I got here. And it’s definitely not how I get better every day.

My first time speaking publicly was in front of 12 people. It went… pretty terribly. My most recent? 5,000 people. Energizing. Easy peasy.

The difference? Practicing. Practicing. Practicing. And then practicing some more.

There are plenty of resources out there for building public speaking skills if that’s a goal of yours. Not here to pile on. I’ll just underscore this: putting in the reps (over and over and over) really matters.

The first few times you flub something on stage? Paralyzing. Debilitating. Full-body, sweaty freakout. But when you’ve practiced, on stage and off, and built a few recovery hacks for when it inevitably happens again? You’re cool as a cucumber. No biggie. You joke. You bring the audience in. You move on. (Or whatever your coping mechanism du jour happens to be.)

Every confident moment you see started somewhere that looked a lot like this. Thank you hairbrush microphones everywhere.

AI Training Fatigue Is Real—Here’s How I Broke Through It.

As a kid, I loved show and tell.
As a professional, I’ve come to love show and demonstrate.

That mindset guided me recently when I spoke on a panel alongside some truly knowledgeable AI experts across industries—Amy “Amy H-R” Hanlon-Rodemich, Billie Jo Nutter, and Vasanthi Chandrasekaram. The audience? A powerhouse mix of industry-diverse scientists, Fortune 500 execs, government leaders, founders, and entrepreneurs – from both inside and outside of tech. People with no shortage of ideas and information hitting them daily.

So how do you make a topic like AI skilling resonate with an audience like that—without drowning them in jargon or fatigue? You demonstrate!

Making AI Skilling Memorable

I used Synthesia (I have zero affiliation) to bring an AI avatar I named Cynthia to life. She opened our panel, welcoming the audience, asking questions, sharing trivia, even cracking jokes. Think awards-show host meets moderator. It wasn’t about showing off the tech, it was about creating a memorable, relatable experience that made AI’s potential click.

And this is the bigger point: AI skilling doesn’t mean you throw out what you already know; it’s about extending those skills with new tools.

  • A marketer who scripts, storyboards, and designs can now spin up multilingual videos at scale.
  • A trainer who builds slide decks can create dynamic interactive learning modules.
  • A product manager who builds demos can deliver personalized walkthroughs across time zones.
  • Heck, a Chief Marketing Officer / Chief Business Officer can skill herself and build an interactive AI video for a speaking engagement.

Business Benefits for Adding AI Generated Videos in your Toolbox

  • Innovation: Enables you to experiment with novel storytelling with dynamic avatars and immersive experience (I had way more fun than building a powerpoint BTW)
  • Scalability: Training, demos, and communications can help teams with lean resources scale.
  • Speed: Content production timelines shrink from months/weeks to days/hours.
  • Consistency: Messaging stays accurate and on-brand every time.
  • Accessibility: Multi-language dubbing enables localization.
  • Engagement: Interactive avatars connect in ways static PDFs and presentations can’t.
  • Efficiency: Lower production costs for lean teams and lean budgets.

While AI generated video platforms are powerful for scale, speed, and accessibility, there are many cases where traditional video production remains the right choice.

High-stakes moments often demand the creativity, nuance, and emotional resonance that comes from working with skilled directors, producers, and film crews. AI-generated video is a fantastic tool in the professional’s toolbox, but it doesn’t replace the craft of full-scale production when the stakes call for it. It’s not about either/or, it’s about knowing when speed and scale matter most, and when human-driven storytelling makes the biggest impact.

For me, it’s another tool in the growing toolbox of an AI-enabled professional. The real power lies in knowing when to apply the right tool to amplify skills you already have.

Key Takeaways

  • Show, don’t just tell: Demonstrations make AI practical, not abstract.
  • AI skilling builds on strengths: storytelling, design, and communication translate into powerful new applications.
  • Tools like Synthesia expand the professional toolbox: enabling speed, scale, and reach.
  • Business benefits are tangible: efficiency, engagement, accessibility, and cost savings.

Smack in the Middle of the AI Skilling Revolution at General Assembly

I also come at this from a unique vantage point. At General Assembly, I’m fortunate to be right in the epicenter of AI workforce skilling—where training, experimentation, and innovation are what we do every day. We’re tool agnostic, but we have the benefit of being exposed to (and testing) many of the innovations emerging in the market. That perspective helps me see both the promise and the limitations of AI tools and why the broader conversation about AI skilling matters so much.

Want to learn more? Empower your teams with in-demand AI skills through hands-on, customizable training, designed to unlock the full potential of AI across your entire organization. From leader to individual contributor, we have you covered.

Implementing a digital worker isn’t just a tech deployment, it’s a people, process, and product orchestration.

We are implementing a digital worker in our contact center named GAbby (yes, clever).

Implementing a digital worker isn’t just a tech deployment, it’s a people, process, and product orchestration. I’m going to build out loud here and share real life reflections from our current implementation (given that General Assembly trains on AI, it only makes sense that we too have it embedded in our own workflows.)

When we implemented “GAbby,” our AI digital worker in our Admissions Contact Center, the pilot was laser-focused on measurable outcomes: throughput, transfer rates, incremental enrollments, and cost savings. We didn’t treat it as a tech experiment—we treated it as a business experiment.

At the surface, implementing an AI-powered agent like GAbby might seem straightforward: feed it some data, map out a call script, and launch. But the reality is far more nuanced. This initiative highlighted several truths about successful digital worker implementation:

1️⃣ Training is as much about guardrails as it is about knowledge.
It’s not enough to train the digital worker on what to say. You must also rigorously define what not to say. GAbby’s early responses hallucinated offerings (like free project management courses) simply because adjacent words appeared together in queries. When AI can access broad public data, constraining its knowledge base to reliable, vetted sources is critical for brand trust and compliance.

2️⃣ Words matter more than ever.
Changing “SMS” to “text message” seems trivial, but this small fix made the agent feel more relatable. The language used by AI must reflect your customer’s voice, not robotic syntax. The user experience is judged on tone as much as accuracy.

3️⃣ Cross-functional collaboration is non-negotiable.
This wasn’t just a “tech project.” Ops leaders framed user scenarios. UX experts evaluated conversation flow. Engineers handled system constraints and testing. Vendors (thx OutRival) contributed platform and expertise. Success only came when these perspectives aligned, especially around what “done” truly looked like.

4️⃣ Personalization requires planning.
Personalizing conversations based on previous interactions or user data makes agents feel smarter, but only if the underlying CRM hooks, lead mapping, and data flows are in place. GAbby’s ability to personalize is promising, but it must be stress-tested across real-world variations and we know iteration is coming.

5️⃣ Launching isn’t the end, it’s the beginning.
Everyone involved treated this launch not as a final product but as a live experiment. There was an openness to iterate based on real interactions. That mindset (launch, listen, learn, and improve) is essential to evolving a digital worker from functional to exceptional.

Digital workers (like GAbby) will increasingly become teammates in service and sales. But without intentional training, thoughtful language design, and tight operational alignment, they risk becoming more alienating than helpful. As this project showed, the AI is only as good as the humans who build, guide, and refine it.

From Skills to Sculpture: How Adobe Connects Creators Across Generations

Every day, I get to witness the impact of Adobe empowering the next generation of creators and marketers through General Assembly‘s partnership on the Creative Skills Academy and our apprenticeship program. But this past week, my family experienced Adobe’s influence in a completely different way: through the Adobe Creative Residency Programme at the Victoria & Albert Museum (V&A).

“Mom, it’s really awesome this exhibit lets you fidget and wear headphones”

“Mom, isn’t it interesting that Luca {Bosani’s} art in the year 2024 explores when a shoe becomes a sculpture and we also saw that small, tall, fancy shoe {huapandi} from the 1800s {a Chinese shoe that was also on display as a sculpture in another part of the V&A}. It’s weird, it’s like every generation and every country has a unique way of experiencing similar things.”

Let me back into both of these quotes.

They came from my 15 year old daughter. My family just got back from a weeklong dream vacation in London and we went to the V&A while there. We knew to go, and to visit the Adobe Creative in Residence programme, because I met the partnership team at Adobe MAX last year.

It was incredible. We got to see the Design and Disability showcase the contributions of Disabled, Deaf, and neurodivergent people. We also explored the works from the 2024 residents Luca Bosani, Jacqui Ramrayka and Rachel Sale and that’s where she made the shoe comment.

In one gallery was a ceramic shoe from 1800s Asia; in another, a modern work by 2024 Adobe Creative Resident Luca Bosani, a London-based multimedia artist exploring the question, “When does a shoe become a sculpture?” Centuries and cultures apart, yet united by a shared instinct to communicate through creativity.

Across time, media, and experience.

Whether in classrooms, museums or at work,  it’s interesting to see how Adobe and GA are helping people express, connect, and imagine across time, media, and experience.

Prompt Skilling Progression and Proficiency

For a business term, I’ll call this something like “prompt skilling progression and proficiency,” but here’s what employee upskilling with AI actually looks like in real life. I’ve seen this play out across teams and orgs of all sizes.

Download PDF of 10-Step Prompt Skilling Progression

Phase 1: Skeptical Curiosity
Fine, I’ll use AI and see what it’s all about. I don’t trust it though.

Phase 2: The First Prompt
Employee opens the AI chat tool of the moment (ideally one with a compliant enterprise account, but this post isn’t about that) and enters something basic like: “Write an email to X person about Y topic.” Wow, cool. That was helpful.

Phase 3: Writing Assistant Era
Employee starts asking the tool for more writing help: “Write an article about X topic.” “Create a blog post about Y.” Dang, that’s awesome.

Phase 4: The Experiment Zone
Now comes the flurry of both serious and fun prompts.
Serious: “Write a memo to leadership about these findings,” with a copy-paste avalanche of fragmented info that turns into a polished output the employee is thrilled to have expedited.
Fun: “Write a funny five-year anniversary note for my colleague Brenda. She’s in Dallas, works in media, loves orchids.” The AI nails it. The employee tweaks it slightly and posts it to Slack or Teams.

Phase 5: Strategic Prompting
The prompts evolve: business plans, project plans, go-to-market strategies, summaries, sales talking points, market scans.
Employee discovers they can upload files, images, and documents. (Hopefully on the enterprise version. Big plug for that.)

This post is about what I see with prompt upskilling, but just to say it: Using public AI tools can pose serious risks if you’re entering sensitive or confidential information. These platforms may store prompts or responses, potentially exposing proprietary data or personal details. That’s why secure, enterprise grade AI tools are essential: they offer data encryption, access controls, and usage governance to ensure your information stays protected.

Phase 6: Prompt Perspective Shift
Then it clicks: you’ve only been prompting “as yourself.” You start giving clearer instructions about what you want back, in what format, and using which inputs.
You learn to prompt as an industry expert outside your role. You ask for sources. You ask for thinking. The AI delivers.

Phase 7: Structured Prompting
Time for a major prompt evolution:
Employee learns to prompt using taxonomies that include role, request, goal, instructions, considerations, tone, style, and output format.
Example: “Act as a strategic marketing advisor with expertise in quarterly planning, audience analysis, and content campaigns across multiple channels.”

Phase 8: Prompt Hoarding
The prompt library begins. Word docs and spreadsheets start piling up. LinkedIn saves stack up. All of it might be useful one day.

Phase 9: Prompt Overload
Weeks pass. Employee is drowning in saved prompt docs across cloud folders and shared drives. Can’t find that one prompt from last week.
Still tries to send them along to help a prompt newbie.

Phase 10: Prompt Infrastructure Seekers
Employee starts hunting for tools that offer a searchable, categorized prompt database to make this curated chaos usable again.
Because the productivity gain of great prompting is now being slowed down… by all the prompts.

Oh, the irony.

What Happens When Sales Leaders Stop Talking About AI… and Actually Start Implementing It?

Representing General Assembly at the Institute for Effective Professional Selling’s AI for Sales Excellence Awards

Last week in Washington, D.C., I had the honor of being on the Sales Game Changers Podcast stage and accepting the Institute for Effective Professional Selling’s (formerly IES) first-ever AI for Sales Excellence Award on behalf of General Assembly.

And I have to tell you, this one meant something special.

Not because it was shiny (it was very shiny).
Not because it was an AI award (and you know I love all things AI training).
But because this award recognizes something deeper… something our industry needs more than hype, jargon, or yet another “state of AI in sales” webinar.

It recognizes doing the work.

Origin Story: Before Our AI Academy Was a Program… It Was Our Own Training

Before we built AI Academy for Sales, we went through the training ourselves.

We were our own pilot group: testing prompts, stress-testing workflows, building repeatable use cases, and figuring out how to strip away the noise and get to what really mattered:

👉 More time with customers.
👉 More listening, less administrative drag.
👉 More problem-solving, fewer “Time Suck Yuck” tasks (yes, that’s the official term now).

Sales professionals don’t wake up excited to update CRM fields, manually prep call notes, or dig through old decks for messaging. They want to solve problems, create impact, and build relationships.

So that’s exactly what we designed our program to enable.

Inside the Episode: Making AI Practical, Not Theoretical

On the Sales Game Changers Podcast, Gretchen Jacobi and I joined host Fred Diamond, alongside the incomparable Zeev Wexler, who sponsored the award, to talk about the very real, very un-glamorous day-to-day shifts that make AI stick in sales orgs.

A few of the themes we discussed:

1. The early AI adopter wins the sale.

“If the early bird gets the worm, the early AI adopter gets the sale.”
Because in a world of buyer noise, the reps who show up faster, more prepared, and more relevant… win.

2. Start small—then scale.

As Gretchen wisely said, start with one low-risk task.
Something uncontroversial, like:

  • Prepping discovery calls
  • Summarizing account history
  • Drafting follow-ups
  • Updating CRM
  • Researching accounts and personas

The wins compound shockingly fast.

3. AI isn’t replacing sellers—it’s releasing them.

Freeing them from low-value administrative work so they can focus on high-value human connection.

At the IEPS event, every awardee said some version of the same thing:
Sales is (and always will be) a relationship business.
AI just gives you the time back to be better at it.

GA’s Three-Tier AI Academy: Teaching Sellers to Sell in the AI Era

One of the reasons we were honored with this award is the structure and practicality of our three-tier AI Academy for Sales, which gives sellers:

🔹 Tier 1 — AI-Enabled Tools

Foundations: prompts, workflows, research, summaries, CRM hygiene, call prep.

🔹 Tier 2 — AI-Augmented Automation

Templates, reusable workflows, sequencing, process improvement, sales ops support.

🔹 Tier 3 — AI-Superpowered Strategy

Predictive forecasting, multi-touch analysis, personalization at scale, revenue insights.

It’s tactical. It’s applicable.
And we use it internally.
Every day.
Because transformation only works when it’s lived, not laminated.

The Award Moment: Why It Mattered

Standing on that stage in D.C., listening to the stories of the other honorees, a unifying theme kept coming up:

Sales excellence is about partnership, problem-solving, and humanity.

The quiet superpower of AI in sales isn’t the automation itself.
It’s what teams choose to do with the time they get back.

More time strategizing.
More time connecting.
More time being the trusted advisors buyers actually want.

That’s what makes AI worth implementing, not just talking about.

The Question I’ll Leave You With

We ask this inside our training, and I’ll ask it here too:

What’s one sales task you’d love to automate with AI so you can get back to the part of the job you actually love?

And if you missed the episode, you can:
🎧 Listen or read the transcript here → https://www.salesgamechangerspodcast.com/generalassembly/

Huge thanks again to Fred Diamond, Zeev Wexler, and everyone at the Institute for Effective Professional Selling for recognizing the work we’re doing at General Assembly to help sales teams thrive in the AI era.

Here’s to less Time Suck Yuck and more time doing what humans do best. ✨

Reflections from the Other Side of the World: A Global Lens on Innovation, Imagination, and Relevance

A Reflection on Global Inspiration

Over the past few weeks, I’ve had the opportunity to travel through Singapore, Indonesia, and Japan—my first time visiting the Asia-Pacific region. While I’ve explored some parts of Europe, Mexico, Canada, and the Caribbean, this journey offered a new kind of exposure: one that reshaped how I think about technology, culture, and our shared global future.

From tasting fresh fruit at a roadside stand in Batam on a taxi driver’s recommendation, to experiencing carefully curated meals in some of the world’s most elevated dining rooms, I was reminded of the simple truth that excellence can be found anywhere. Each moment offered its own kind of richness and helped deepen my appreciation for what different places bring to the global table.

Achieve Ambitious Goals through Partnership

As someone who has spent the last 20 years in EdTech (from digital marketing and app development to higher ed transformation and workforce reskilling) I returned home feeling deeply inspired and just a bit changed. The conversations I had across these countries, many of them with technical leaders in areas like machine learning, robotics, semiconductors, fintech, and AI policy, left me reflecting not only on the future of work, but also on the partnerships and coalitions we need to achieve ambitious goals for people and society.

A more personal takeaway: I found myself asking how I stay relevant and bold in the face of such rapid innovation. Being in rooms filled with brilliant minds challenged me, in the best way, to recommit to curiosity, conversation, and collective problem-solving. It reminded me that progress isn’t linear. It’s a cycle of learning, adapting, and improving…with plenty of pivots along the way.

The roles we’re training people for today don’t exist yet

I’m currently reading The Dip by Seth Godin, which challenges readers to become the best person for a specific job at a specific moment. It talks about the extraordinary benefits of knowing when to quit and when to push just a tiny bit longer to find your breakthrough. That idea feels particularly relevant in a world where the roles we’re training people for today may not even exist tomorrow. The workforce is evolving so quickly that orienting around durable skills, mindsets, and learning agility feels more essential than ever.

On a more practical note—after flying through the airports in Singapore and Tokyo (and seeing images of Dubai’s), I may never look at MCO, ATL, LAX, LGA, JFK, or MDW the same way again. Let’s just say we have some catching up to do.

Why wonder still matters in a world of rapid change

One of the most unforgettable experiences was visiting teamLab, an immersive digital art museum in Tokyo. It felt like stepping inside pure imagination. What struck me most wasn’t just the visual beauty—it was how the experience evoked awe, wonder, and joy in every single person. Grown adults stood wide-eyed, mouths open, transfixed. It reminded me that as we grow older, we don’t often grant ourselves space to be overwhelmed by wonder. Parenting may offer glimpses through our children’s eyes, but this experience gave it back to me directly.

And it left me asking: What would happen if we protected our capacity for wonder the same way we protect our strategic plans?

This journey was a gift—personally, professionally, and philosophically. I return with new questions, fresh energy, and a deeper appreciation for what’s possible when we connect across borders, disciplines, and ideas. And maybe, most importantly, a little more imagination.

Press and Interviews

e27 Asia: Upskilling in the AI era: Why passive learning will not cut it anymore
By Anisa Menur A. Maulani | April 29, 2025 | “Upskilling initiatives should be embedded into the company’s strategic roadmap,” Hathaway says. “They must be directly applicable to business objectives and support employee mobility and retention. Without this alignment, training risks becoming irrelevant.”

Channel News Asia (CNA): Upskilling in the AI era: Why passive learning will not cut it anymore
By Cheryl Goh | March 19, 2025 | Fresh out of school and struggling to get a job? You could be lacking some skills. While technical skills are important, industry experts say many more applicants lack interpersonal proficiency. What are these, and are they innate or nurtured? Cheryl Goh talks to Jourdan Hathaway, Chief Business Officer of General Assembly – a global pioneer in tech training and talent solutions.

Lessons from an Automation Fail

Many years ago, I had an epic automation fail that taught me a big lesson in tech implementations. It’s the kind of lesson you only need to learn once before it changes your understanding of the success drivers during digital transformation. My buddy Corey Miller would refer to this as a Red Learn (fail) and a Green Learn (growth).

I’m an operator, so naturally I look for ways to drive efficiency, optimizations, and scale.

Imagine you had to manually send out application deadline emails every 8 weeks, for 800+ different online programs, across 60+ education institutions day in and day out. This is a perfect use case for email automation (table stakes today, but novel back in the day). Let’s zip past the 💪Herculean effort to gather business requirements, select the vendor, do the implementation and customer config. This isn’t about that.

Let’s just get to the part where we built a great master template that had a bidirectional sync with all the necessary compliance, content, and data to power a single automated program (where operators swoon). This template pulled in 26 dynamic content field to ensure it matched the right program and institution – things like, the actual deadline date, the school name, the logo, the program name, the key value props, tuition cost, apply now link, etc.

So what happened?

The automated program worked as intended technically speaking. But here’s where the ‘uh-oh’s were:

  • Among those 800 different program names? Masters of Business Intelligence was spelled wrong (🤦‍♀️face palm for being spelled Intellgence) in the original CRM set up that it pulled from. That field was never intended to be public facing and so it wasn’t QA’d back in the day. Just correct the typo you say? We did, which then broke 11 different business reports that were integrated with that data field. Other departments depended on those reports – not great.
  • How about that easy date field? 🤦‍♀️Uh-oh, we didn’t accommodate the day/month vs month/day formats across countries. We just manually knew to reformat.
  • How about that tuition field? 🤦‍♀️Uh-oh, we didn’t have a data governance protocol for ensuring all 800 programs were maintained with price adjustments as time went on.
  • How about that Apply Now link? 🤦‍♀️Uh-oh, several pointed to a URL that we didn’t have control over and no mechanism to know if it changed and thus gave recipients a 404.

Here’s the big learn: Your data is the foundation of success; so are the business processes around data governance and maintenance. Do not underestimate this part. If you’ve seen this movie before, it doesn’t matter what tech project you’re working on, you enter it with a healthy respect for your data strategy.

It’s also why you know that implementation will be 20-30% longer that that lovely original timeline if your data strategy is not ready. But, this all solvable. And it’s a skill. So go thank and fist bump the Business Analysts, Data Folks, PMs, Delivery, and Process/Workflow people in your life.

What makes a team high-functioning?

“Ok, here’s the roadblock, but we can totally figure this out. I have a plan on how we can tackle it.” ⏳ 4 hours later…..

“Ok team, thanks for the rapid problem-solving meeting. We’ve now prosecuted the plan. Triage is underway. To recap, I’ll do this. You take that. She’ll own this part. He’ll own that other part. Now let’s go deliver! We’ve got this. See you back here in 24 hours to confirm our collective resolution and success.”

What to do when you hit that inevitable project roadblock

The above are conversations that transpired on a super thorny, complicated, tech project. Hitting a roadblock on a technical project itself is never a surprise. C’mon, you know the kind – tons of systems, tons of competing priorities, tons of stakeholders, not enough time, unforeseen downstream impacts of something not operating as intended (say what? never). Then that heat that envelopes a team nearing the go-live deadline – and 💥 – big roadblock emerges and someone has to call an audible.

We overcame such a project this week and it had me thinking about what makes a team high-functioning. I saw it in action. I was in the thick of it with them (and I’m morbidly captivated to moments like this because I’m obsessed with the power of human connection and its resulting achievements). Days later, I’m still reflecting on how proud I am of what the team overcame and ultimately accomplished – not just the ‘what’, but our ways of working (and treating each other) while doing the ‘what’.

I’ve routinely noticed 2 FEELINGS that make all the difference:

  1. Trust (I trust my co-worker to do his/her part and they can count on me to do mine)
  2. Winner’s Mindset (I believe we can conquer this and find a successful path forward)

High functioning team members have innate accountability

My next observation after calling the audible was our Head of Product Marketing saying, “I understand the roadblock and I have a triage plan we could rapidly execute to navigate this. It comes with tradeoffs so let’s assemble the team now and prosecute it.” She did this unasked with total ownership. Then our Senior Technical Product Manager did the same thing, but on the technical side.

Back the “what” – here’s what the team did:

uh-oh moment ➡️ project audible called ➡️ roadblock identification ➡️ areas of ownership established ➡️ rapid problem-solving as a group ➡️ plan created ➡️ tradeoffs explored ➡️ expectation setting ➡️ stakeholder alignment on triage-plan ➡️ divide and conquer to execute ➡️ plan activated

This all happened in hours – not days and weeks, HOURS.

Today we celebrated that we ‘did the thing’. Internal comms went out about our go-live and the action plan to finalize all the remaining to-dos. Remember those tradeoffs? People typically won’t be upset about tradeoffs so long as you set clear expectations and get buy-in along the way.

This is where it’s important to have durable skills, not only hard technical skills.

A CMO’s Perspective on How AI is Changing the Marketing Discipline

No tech skill is animating today’s business leaders and workers alike quite like artificial intelligence. As AI redefines the future of work, organizations are faced with the critical task of building, re-skilling, and augmenting their workforce. This is certainly true of the marketing discipline as well.

3 Ways Marketers are Leverage AI

  1. Within our existing marketing tools – This is where new features are being rolled out within our existing embedded industry tech stack that augment productivity (like Adobe Express with an embedded AI image generator and AI assistants. AI is being implemented in our standard MarTech tools – from media buying and email automation tools to project management and content platforms). Take the project management AI assistant; we use it for automating answers, summaries, tasks, field completion, milestone creation, and updates.
  2. Individualized blue sky use – This is where marketers are creating their own role-specific use cases. Marketers are looking at time spent on manual repetitive operational tasks (very unique to their specific to-do list) and figuring out how to leverage AI. A few examples: one marketer on my team cut down by 85% the amount of time spent on identifying spam leads in a big .csv file. They did a prompt on what to look for and it also provided the Python input. I have another marketer who uses it to draft requirements documents as a starting point, and many content creators are obviously leveraging it.
  3. Novel marketing capabilities – This is where AI is unlocking completely new ways to engage audiences, leverage data, and drive innovation. We’re now able to tap into capabilities that previously seemed aspirational but are becoming reality through AI’s rapid evolution. For instance, AI is enabling hyper-personalized marketing at scale, allowing us to dynamically tailor messages, offers, and creative content to individual preferences and behaviors in real-time. Predictive analytics and learning models are also transforming customer insights, enabling us to not only anticipate needs but also actively shape customer journeys in more intuitive, responsive ways. We recently piloted an AI admissions rep (i.e., a simulated representative) who now conducts the initial conversations with students via call, text, and email. Key to this is using the right company-owned data to ensure we give prospects correct information.

AI’s Impact on Marketing Isn’t Just for Increased Productivity; It Also Impacts Cost Efficiency

We’ve seen an 18% decrease in cost per lead through AI-based campaign optimization. By analyzing vast amounts of behavioral and contextual data, AI can now recommend optimal ad placements, creative choices, and delivery timings based on precise customer segment analyses. Continuously optimizing campaigns to improve budget efficiency, while saving time on manual analysis. Important to this:

  • Success is predicated on the quality of your AI model – must have quality data inputs from trusted sources. Ideal customer profile and accurate targeting.
  • Marketing teams need to be upskilled to have basic data analytics skills. They can’t trust AI if they don’t understand the inputs/outputs.

We Have to Rapidly Close the Skills Gap for AI in Marketing

We see a massive skills gap that the marketing industry needs to address if we want to see a sustainable long term pipeline of tech savvy marketing talent.

At General Assembly, We partner with employers to help them upskill their marketing teams for the AI era. Let me give you a concrete example: we work with Adobe to create a pipeline of young, tech savvy creative and marketing talent. Two new General Assembly bootcamps on marketing and content creation are enrolling students from communities underrepresented in tech – with Adobe covering all costs for them.