Hi there,

The July summer is one of the most productive times of year for me and my time. We are increasingly preparing for the Emerald Summit this September. At the same time, I’ve been developing more assets for my AI Revenue Engine (AIRE) program. 

👉 It’s an exciting time to be at the forefront of technology, governance, and fintech. 

In this issue, I delve into startup growth playbooks from two amazing founders . I also touch on how you can turn being invisible into a competitive advantage in your company, valuable insights into measuring AI effectiveness, and current agentic AI trends across industries. 

Send this to a friend or colleague who is looking to implement AI in their operations but isn’t sure where to start. They’ll thank you for it. 🙂

Upcoming Events

Don’t Forget: Emerald Summit Early Bird Discount (Sept 18)

The Emerald Summit is Wallet Max's flagship Climate Week NYC event and you can join us this year on September 18 in New York. The summit sits at the intersection of NYC Climate Week, the UN General Assembly, and NYC Fashion Week, drawing startup founders, impact investors, corporate executives, policymakers, and media focused on climate, fintech, and AI.

The day runs from 9:00 AM registration and breakfast through a full agenda of keynotes, panels, and fireside chats covering topics like climate finance, the circular economy, climate resilience, renewable energy policy, and unlocking capital flows for climate solutions. Attendees will also enjoy a Startup Pitch Competition and our award ceremony.

Great news: Early Bird pricing for the Emerald Summit is available through July 31st.

👉 TODAY is your best shot at locking in the lowest rates before they're gone.

When you participate in Emerald Summit, you’ll get a chance to network with investment leads and talented founders like:

• Betsy Fore, Velveteen Ventures

• Bhuva Shakti, Wallet Max

• Blair Carl Smith, Milken Institute Financial Markets

• Cody Ley, Hemp for Humanity

• David Chan, Homestead Capital

• Elana Margulies-Snyderman, EisnerAmper

• Enes Karakullukcu, Klaris Capital

• Marc Robert, Water Asset Management

• Ophir Bruck, CDP

• Parichat Wrolstad, University of Exeter

• Sacha Awwa, SAMG Marketing Group

• Scott Ryan, Investature

• Sonam Velani, Streetlife Ventures

• Will Hogan, Umergence

🎟️ There are many ways to join us in September. Pick your preferred ticket:

• Early Bird – Summit Only: Full-day access to the Emerald Summit (speakers, keynotes, panels, pitch competition, startup awards, breakfast, lunch, refreshments, networking). Limited to 50.

• Early Bird – Dinner Only: Evening-only access to the VIP Dinner (mocktails/drinks, hors d'oeuvres, 3-course family-style dinner). Limited to 10.

• Summit & Dinner (Best Deal): Combines full-day Summit access with the VIP Dinner. Limited to 40.

Save your seat today: luma.com/EmeraldSummitWM26

Past Event Highlights

Dive into key learnings from the past few weeks of in-person/virtual community events.

Design AI Workflows That Deliver Business Results

Organizations rarely fail because AI technology fails. They fail because workflows, accountability structures, and operating models don't evolve alongside it. Implementation is often the easy part; capturing value is harder.

Companies frequently spend more time selecting vendors than redesigning how decisions and responsibilities will actually change.

But organizations across industries can tap into showing gains such as improved adoption rates, reduced downtime, and faster cycle times once workflows are redesigned before or alongside AI rollout.

The AI Revenue Engine (AIRE) methodology has three pillars: Revenue Growth, Smart Operations, and Business Agility. These act as the lens for evaluating whether AI initiatives connect to real business outcomes rather than technology for its own sake. 

➡️ Watch this → full masterclass

Build AI Capabilities That Scale With Your Business

Why do successful AI pilots so rarely scale? 

Pilots validate technology, but scale validates the organization. There are five capabilities that separate companies that scale AI from those stuck in permanent pilot mode: leadership, operations, data, governance, and workforce readiness.

The throughline: AI doesn't fail because the technology breaks. It fails because organizations haven't built the accountability, governance, and operating discipline to sustain it past the demo stage. In this masterclass, I walk through real examples where standardizing operating models and strengthening executive sponsorship turned stalled rollouts into enterprise-wide wins, often without any additional technology spend.

This session ties together the full AIRE framework, Revenue Growth, Smart Operations, and Business Agility, into a practical roadmap for building lasting AI capability, not just isolated wins. 

➡️ Watch this → full masterclass

Measure AI Success Beyond Technology Metrics

Activity metrics like adoption rates, model accuracy, and usage volume measure what happened, while business metrics measure what mattered. Companies can hit 90%+ adoption and still see stagnant revenue or rising costs if leadership is tracking the wrong things.

In this AIRE Masterclass, I lay out a five-category executive scorecard, revenue, productivity, customer outcomes, risk, and people, paired with both leading and lagging indicators. I argue that dashboards should stay simple: 5-10 metrics that drive decisions, not 100 that bury them. I also reframe AI ROI as a capital allocation discipline, not a one-off tech expense, urging leaders to fund what demonstrably works and cut what doesn't.

Consider this question: If you stripped every technology metric off your dashboard tomorrow, would you still know whether AI is improving your business? If not, you're measuring the wrong things. 

➡️ Watch this → full masterclass

Stop Funding AI That Doesn't Deliver

Organizations are investing heavily in AI, pilots are expanding, budgets are increasing. But not every AI initiative deserves more investment.

One of the hardest decisions leaders face is knowing when to continue, when to redesign, and when to stop funding an AI initiative that is not delivering measurable business results.

The challenge is not simply measuring AI performance.

In this session, I explore how leaders can evaluate AI initiatives, identify where business value is being created, and redirect resources toward opportunities that deliver stronger returns.

Learn how to evaluate AI initiatives, identify early signs of low-value AI investments, and more in this recent masterclass.

Get all the details in the replay 👇

Startup Growth Playbook: LIVE Interviews

How AI is transforming banking intelligence

In this episode of Startup Growth Playbook, I interview Adnan Haider, co-founder of Quantuma, a deal intelligence platform helping commercial banks uncover revenue opportunities across their client base. Adnan previously served as SVP of Analytics at fintech unicorn Zafin and led advanced analytics at IBM Canada, and now teaches product management at the University of Toronto.

Adnan traces Quantuma's origin to a gap he saw firsthand: relationship managers at commercial banks juggle hundreds of client relationships using fragmented internal systems and almost no external data, leaving all but their top clients underserved. Quantuma's "deep reasoning AI" layers on top of traditional analytics, synthesizing transaction data, regulatory filings, and CRM history to surface which clients need which financial products and when.

He reflects candidly on the jump from corporate leadership to founder ("everything becomes your problem"), the importance of locking in design partnerships early, and why, in regulated industries like banking, trust and relationships outweigh technology or metrics when closing deals. He also predicts that AI won't replace relationship managers but will raise the bar for what "doing the job well" means, making human relationships more valuable, not less.

Asked about what's driving his current approach, Adnan pointed to staying close to the work itself:

"It just makes a lot of sense to be hands-on right now... it's possible to do so much more than what was possible last year or definitely two years back, but all of it requires being hands-on and not being a manager... there's a lot of satisfaction and impact that comes with being hands-on and almost being an individual contributor again."

Don’t miss this engaging interview with real-world tips. You can see the full Playbook episode below 👇

How Agentic AI is Transforming the Nutrition Industry

In this episode, Pallavi Jain, technical co-founder of Mood Eater, breaks down how her agentic fulfillment platform replaces menu-browsing and chatbot prompting with automated, biology-aware meal recommendations. Pallavi's background spans life sciences, econometrics, and consulting, where she learned the clinical rigor of food-drug interactions and the discipline of validating data at scale.

Her motivation is deeply personal: raised in a Jain household with strict food-pairing traditions, and shaped by losing her father as a child, she built Mood Eater as both a practical tool and a mission: to promote mindful, plant-forward eating and reduce animal suffering. 

The app onboards users through a quick "mini-game" capturing health goals, allergies, medications, and wearable data, then surfaces pre-vetted, swipe-based meal picks, no prompting required, sourced only from A-rated restaurants and reviewed by a human doctor in the loop, since she believes current AI still can't reliably access or synthesize deep medical research on its own.

Asked what sets Mood Eater apart from convenience-first apps like DoorDash, Pallavi described her secret sauce:

"I think the biggest use case for AI is actually hyper-personalization. I think all of us have been fooled by just using AI through a chat interface. I do not think chatting is the best use case of AI... Why do I have to browse so many websites or read so many novels? Why can't you just hyper-personalize my specific context for me to move ahead faster? That's where I think the power of AI lies."

Tap into all the insights in the replay below 👇

AI Trends Worth Watching: What Matters Now

Many businesses are facing a core question: “Should we adopt AI.” But the organizations pulling ahead are the ones that built the operating model, the data foundation, and the governance rhythm before scaling the tools. Not after.

Take banking, for example. Banking is graduating from chatbots to agentic operations. The conversation has shifted from whether to use AI to whether institutions can operationalize it faster and more safely than competitors. Banks are moving past employee copilots into agentic AI that can plan and execute multi-step workflows, update records, and escalate decisions.

That operating-model shift isn't hypothetical but structural. At Data Summit 2026, Airo Digital Labs' Michael Vasicek argued the operating model itself is changing: fewer levels, with every employee both assigning and receiving tasks from AI agents, and taking responsibility for auditing agent results and correcting "agentic drift". Governance has shifted from a side conversation to a job description.

Manufacturing shows what happens when governance is skipped. Four in five U.S. manufacturing facilities still operate with zero automation. Facilities without clean, structured data and secured operational networks can't reliably deploy modern automation, no matter what the vendor promises. I say this constantly: readiness comes before rollout, not after.

On the vision and robotics side, the same story repeats. One of the biggest roadblocks to AI adoption has been complexity and risk, and platforms are now emerging to simplify multi-camera, real-time inspection deployments with built-in security and clearer ROI. And AI's power in classification and defect detection only shows up when it's paired with expert system design tailored to the specific manufacturing context.

And the market is already pricing in who's ready. JLL's new research is the clearest signal yet: markets most exposed to AI-driven job displacement are also seeing the strongest real estate demand from AI companies, with San Francisco alone drawing nearly 30% of total leasing from AI firms since 2025 despite carrying among the highest displacement-risk profiles in the country. 

The takeaway echoes what I tell clients: a market's or company's capacity to adapt matters more than its exposure to disruption.

If your leadership team is sitting on AI pilots without a clear path to measurable revenue or operational results, that's precisely the gap AIRE™ was built to close.

👉 Happy to talk it through → bhuva.biz/aire

The BIG Blog Digest

Still time for some reading? Here are some articles of interest this month.

How to Translate AI Adoption into Measurable Business Results

AI adoption fails to deliver business results when organizations implement new technology without redesigning the underlying workflows, accountability structures, and processes it operates within. Real transformation, and measurable outcomes like revenue growth, operational efficiency, and agility, comes from redesigning how work gets done, not just deploying AI tools. Read this full blog here.

AI adoption succeeds when business goals, workflows, and accountability move together

AI initiatives often achieve strong technical implementation but fail to deliver business results when strategy, priorities, and accountability aren't aligned across leadership and functional teams. Sustainable value comes not from better AI tools but from aligning business goals, workflows, and ownership before and during deployment. Read this full blog here.

AI’s Energy Demand Is Surging. Are Our Systems Ready?

AI's rapidly growing energy demand, potentially doubling US electricity use by 2028, risks straining power grids and disproportionately harming vulnerable communities, schools, and families unless infrastructure and equity planning keep pace with innovation. Emerald Climate Summit during NYC Climate Week in September to bring together AI builders, energy funders, and policymakers to address this challenge collaboratively. Read this full blog here.

Risk Lesson: Systems Reward Those They Resemble

One of the hardest lessons I had to internalize, especially on Wall Street. was that competence doesn’t always speak for itself. Systems tend to reward familiarity. They reward what they recognize. And more often than not, that recognition is shaped by legacy patterns: who’s been in the room before, who speaks the dominant dialect, who fits the profile of “safe.”

That’s not meritocracy. That’s mimicry.

In the early years of my Wall Street career, I would walk into rooms where my presence was both novel, and at times, invisible. I remember one particular meeting where I was asked to present a risk mitigation plan I had architected over several weeks. As I began, a senior leader interrupted me and asked when the “real project lead” would be arriving. I was the real project lead.

I didn’t react emotionally. I responded with data, diagrams, and solutions. And by the end of the meeting, that same person asked me to join a follow-up strategy session. But I didn’t celebrate it. Because I knew what I had earned wasn’t inclusion but an exception. And exceptions are not system changes.

What kept me grounded was the recognition that my difference wasn’t a deficit. It was a diagnostic tool. I saw things others missed, not because I was smarter, but because I was outside the assumed norm. I could identify hidden risks, overlooked biases, and broken processes.

This is why representation matters. It’s not about optics. It’s about outcomes. Systems don’t evolve through sameness. They evolve through dissent, through divergence, through the courage to say, “What if we built it differently?”

In my book, Everyday Risk Wisdom: Your Risk Management Guide to Thrive in a Complex World as an Overlooked Business Leader, discover how I work towards changing the system and action steps for reframing differences as advantages.

Explore my book website below and get notified when this lesson is available for free!

The BIG Reflection Quiz

There are multiple ways to deal with being “the other” in a broken system. Which mindset do you employ when trying to change the system?

• I reframe the difference as an advantage.

• I mentor others who are “invisible” to the system. 

• I use my seat at the table to include more people from outside the system.

• All of the above.

• I’d do something else…(shoot me a message and let me know)

Read the lesson for my “Systems Reward Those They Resemble” action steps. Explore my book website below and get notified when this framework is available for free!

Join me in September

While I continue to assist founders and organizations with AI through AIRE, Emerald Summit is approaching rapidly. 

I’d love to have you there, and there are many roles open beyond simply attending. I and the Wallet Max team are looking for sponsors, startups, and volunteers. If you’re looking for a way to get involved, this is the call!

And if you’ve already got too much on your plate but you still want to attend Emerald Summit and the Wallet Max Bold World Awards, don’t forget to pick up your early bird tickets before July 31st.

Until next time, I wish you a successful month building your planet-positive business!

Thank you for reading so far, and we look forward to having you on the journey.

Onward and upward,

Bhuva Shakti, Founder of Wallet Max and Bhuva’s Impact Global.

Let’s collaborate, send me your ideas! www.bhuvas-impact.global/bhuva