Is Your Company Profiting from AI? #6

1. Introduction

You will not unlock AI's true potential by simply deploying it in your company (Forbes, 2026). GenAI disruption varies by industry (MIT, 2025), but the fundamentals of success are the same. In this edition, I will outline how you can use it to harvest value in your company.

2. The Token Market Overview

Until recently, AI tools like ChatGPT didn't learn, integrate, and match business workflows efficiently, making it hard to deploy (MIT, 2025). Before AI, companies invested heavily in developing or acquiring software. Now there are tools with enough context windows and memory to build systems adapted to custom business rules.

Even non-software companies started building proprietary systems using agentic AI. In this sense, Tallis Gomes, cofounder of G4, says building with AI is faster and cheaper than acquiring software through M&A (Infomoney, 2025). Indeed, not every company will develop its own systems since someone has to identify the most important business problems, decide what to build, maintain it, and own it when it breaks (Bernard Marr, 2026; bizzy, 2026).

Regardless of who handles software development and maintenance, successful firms focus on solving specific business problems, and generic AI tools fail when you need systems that adapt, remember, and evolve (MIT, 2025; Forbes, 2026). According to the MIT report "The GenAI Divide - State of AI in Business 2025":

"Despite $30–40 billion in enterprise investment into GenAI, this report uncovers a surprising result in that 95% of organizations are getting zero return."

We entered the token economy, and it's reorganizing the global economy, bringing a new resource dependency (Gilles Raymond, 2026). Even Y Combinator (2026) is suggesting entrepreneurs should tokenmax (meaning: to maximize the consumption of AI tokens to signal high productivity). Without a clear strategy, it's easy to follow the hype and blindly increase costs. I see tokenmaxxing as a vanity metric.

The McKinsey report "The state of AI in 2026: On the road to ROI" states that AI is enabling notable improvements in innovation, competitive differentiation, customer satisfaction, and employee satisfaction (McKinsey, 2026). On the other hand, what about profits? It remains the same as in 2025.

I've been studying agentic AI for almost a year and learned that before automating a process, it's better to simplify and streamline it before scaling and assess if it really needs automating at this moment or at all. Using AI to build can be fun, but it should be used strategically to solve specific problems that deliver ROI.

Your understanding, access to quality information, and skill to provide context to the AI will define the quality of the results. Don't follow other companies' AI deployment strategy; learn from them but build your own. Copying and pasting is risky. Know your numbers, and measure the impact of your AI initiatives.

High-performing companies, according to McKinsey (2026), pursue growth and innovation alongside efficiency. They redesign workflows around AI instead of inserting it into already existing workflows, and they pair every deployment with the leadership commitment and operational rigor needed to turn it into a real gain. That is the gap between organizations still stuck at individual productivity and the ones converting AI into financial impact.

AI is no longer a futuristic idea, and it is already woven into every industry (World Economic Forum, 2022). Workforce AI literacy is what determines whether a company captures that shift or gets caught by it.

Getting better at AI is not about mastering one platform. AI products change too fast for your workforce education to revolve around a particular platform (Chen, 2026). Professionals need to understand how AI systems work to assess outputs, recognize limitations, and make informed decisions as new tools emerge.

Designed by the author (2026). Adapted from AI in Business (2024).

The four areas in the image above represent how the workforce should plan and maximize efficiency instead of tokenmaxxing to achieve profitability. A team that knows how to interrogate an AI output, not just prompt one, is the team that turns the market shift described above into financial impact instead of another item on the vanity-metrics pile.

3. Conclusion

Deploying AI is not a strategy, but using it to solve specific problems is. That is the line separating the 95% of organizations still waiting on returns from the high performers already converting AI into growth, innovation, and financial impact. The gap is not access to tools. It is judgment: knowing which problem is worth solving, what to build, who owns it, and how to read what the AI gives you back.

Tokenmaxxing will not close that gap. Neither will copying another company's deployment strategy. What closes it is a workforce that treats AI literacy as a discipline, not a feature of one platform, and a leadership that governs every deployment with the same risk assessment and care it would demand of any other capital investment.

Build that capability in your company. Measure it against your own numbers. Then, the market shift already underway will become your gain instead of your cost. Subscribe to keep up with ideas on Changemaking, Sustainability, Tech & Business.

4. References

AI in Business. (2024). AI in business: Case studies and success stories [Video]. YouTube. https://www.youtube.com/watch?v=0PFGmyVTTV4

Chen, H. (2026, August 25). Building AI literacy. Food Technology Magazine. https://www.ift.org/food-technology-magazine/building-ai-literacy

Firth-Butterfield, K., Anthony, A., & Reid, E. (2022, March 17). Without universal AI literacy, AI will fail us. World Economic Forum. https://www.weforum.org/stories/emerging-technologies/without-universal-ai-literacy-ai-will-fail-us/

Marr, B. (2026, August 10). 8 companies proving AI can deliver real ROI. Forbes. https://www.forbes.com/sites/bernardmarr/2026/08/10/8-companies-proving-ai-can-deliver-real-roi/

MIT NANDA. (2025, July). The GenAI divide: State of AI in business 2025. https://cloudelligent.com/wp-content/uploads/2026/02/v0.1_State_of_AI_in_Business_2025_Report.pdf

Raymond, G. (2026, March 25). Welcome to the token economy. Edgee. https://www.edgee.ai/blog/posts/welcome-to-the-token-economy

Tinkoff, D., Van der Veken, L., Chui, M., & Balakrishnan, T. (2026, August 25). The state of AI in 2026: On the road to ROI. McKinsey & Company. https://www.mckinsey.com.br/capabilities/quantumblack/our-insights/the-state-of-ai#/

Y Combinator. (2026). Tokenmaxxing: How top builders use AI to do the work of 400 engineers [Video]. YouTube. https://youtu.be/57lDpTwiW6g