Don’t Invest in AI, Lead With It: The Six TEAs Transforming Smart Companies
If you’re still asking, “Where are we investing in AI?” you’re asking the wrong question.
This isn’t 2017. AI is no longer some speculative R&D moonshot. It’s not a gadget you bolt on to your existing business. AI is the internet of this era, a platform shift so foundational, it’s reshaping how organizations operate, compete, and win.
So why are so many leaders still looking at it through the wrong lens?
It’s like asking in the late ’90s, “Where are we investing in using the internet?” Instead of asking where you’re investing in AI, the question should be: How are you leading with it?
Enter the Six TEAs of AI.
Time. Energy. Attention.
According to leadership expert Scott Thomas, these are the real currencies of transformation. And the Six TEAs of AI Leadership show exactly where to focus them. This isn’t theory. It’s a practical, high-leverage playbook for where to start integrating AI across your organization, and building a strategic edge that your competitors can’t catch.
Let’s break them down.
1. Enabling Solutions (Quick Wins)
Not every AI deployment needs to be moonshot-worthy. Some just need to move the needle first.
Dashboards that deliver smarter insights. Copilots that guide sales conversations. Automations that eliminate tedious, repetitive tasks.
These are the fast wins that build internal confidence and allow to start to experiment and get smart on the “over the counter” solutions on the market for relatively low cost. They remove friction, create ROI visibility, and lay the groundwork for broader adoption. Think of them as your AI training wheels, only they actually go somewhere.
2. Technical or Industry Specialization
The biggest AI breakthroughs won’t come from generic chatbots or off-the-shelf tools. They come from domain-native intelligence.
If you’re in healthcare, imagine AI that supports clinical decisions in real time. In manufacturing, you’re likely already considering systems that fine-tune production without human intervention. In finance, algorithms that anticipate risk before it materializes.
This isn’t automation. It’s strategic differentiation and hyper focused on your specific space. Leaders embed AI into the DNA of their domain, and this is one of the larger hurdles for organizations.
3. Data Strategy & Contextual Visibility
Here’s the hard truth: if your data is a mess, your AI strategy will struggle to really take flight.
Siloed systems. Dirty datasets. Inaccessible knowledge. Or now digital data footprint for parts of your business will limit you now and into the future.
Elite organizations treat their data like a strategic asset, not a byproduct. If their data isn’t already in a state ready to be leveraged, then they have a plan to get there.
AI runs on context. And context lives in your data.
4. Institutional Intelligence Platforms (“Fenced” LLMs)
What if every employee had an AI assistant trained not just on general knowledge, but on your company’s workflows, processes, playbooks and unique cultural nuances?
Internal large language models (LLMs) do just that. They create a shared brain across your organization. A living system that reduces onboarding time, drives operational consistency, and scales institutional knowledge.
When done right, this isn’t just a tool. It’s your internal OS. In the near term virtually all companies will have one. Say good bye to shared drives, binders of SOPs and internal wikis.
5. Agentic AI
Most don’t start here, but as you get smarter on the above, you start to prioritize pain points within your organization and where you have the most opportunity tied to automation.
Agentic & Automated AI; helps you pursue outcomes, execute tasks, manage workflows and perform functions without constant human interaction.
The equivalent of junior team members for your team who are “always on”.
6. Development Processes & Tools (for Tech Organizations)
If you’re in the business of building technology, integrating AI into your development lifecycle is no longer optional.
AI-assisted coding. Automated test generation. Faster release cycles. The goal isn’t 20% efficiency gains—it’s 5x output. Senior devs using AI right should look like productivity superstars.
In tech, this isn’t a luxury. It’s survival and if you’re a technology CEO this is already keeping you up at night.
The Real Playbook for AI Leadership
The Six TEAs aren’t a checklist. They’re a compass.
You don’t have to master all six overnight. But you do need to be investing in at least three and aligning them with your strategic objectives.
AI transformation must be led by executives, not by technical teams or junior employees.
If you’re in vertical market software, the clock is ticking. AI isn’t coming. It’s here. And the leaders who act now won’t just compete—they’ll dominate.
So ask yourself:
- Would it be a terrible idea to see how your organization stacks up against the Five Obsessions of Elite Organizations?
- Is it ridiculous to consider that your data strategy might be your biggest hidden asset or liability?
- Would starting a conversation with a team of seasoned business guides be a waste of your time?
If the answer to any of those is “No,” then it’s time to move.
Next Steps
- Start by picking up a copy of our book, Five Obsessions of Elite Organizations, on Amazon, Audible, or at FiveObsessions.com.
- Take the Elite Organizations Assessment and find out where your company stands in the Five Obsessions.
- Or meet our team at Next Level Growth to explore how to start leading with AI.
Because by the time others figure out where to start, you’ll already be leading the pack.
