What Every CXO Needs To Know About AI

For many companies, AI is starting to affect every function, from marketing and finance to supply chain and customer service. It offers leaders sharper insights and helps teams make faster and better-informed decisions. At this point, choosing to ignore it is effectively choosing to ignore business growth.

I still see organizations treat AI as something to layer on top of what they already do. That approach rarely works. AI isn’t optional anymore; it is becoming as critical as accounting, HR or IT infrastructure. And yet adopting it without a plan can be just as dangerous as sitting it out. That’s why CXOs need to think carefully about how to utilize AI best, leading with both curiosity and caution.

The Business Case For AI

On the revenue side, AI boosts personalization, product development and pricing strategies. It helps companies reach customers more effectively and bring new offerings to market faster. On the cost side, AI supports automation and improves forecasting to help allocate resources more efficiently.

At the same time, AI has to be trained, monitored and continually adapted. Think of it almost like raising a child, requiring high-quality input, clear boundaries and consistent feedback. Without proper structure, it can wander into unexpected, sometimes undesirable behavior.

I’ve seen manufacturing clients who want to use AI for quality control, having the system identify whether parts are correct or defective. The challenge was that it took thousands of images before the AI could reliably distinguish what was “good” from what was “bad.” The lesson: Without the right training and data foundation, AI doesn’t give perfect results instantly.

The Playbook For CXOs

There are a few guiding steps I think every CXO should consider when adopting AI.

1. Define clear use cases. The first step is identifying where AI can actually solve a real problem or create value. Don’t adopt it just for its own sake. If you don’t know what you’re solving for, AI can just create more confusion. Pick a use case, develop a prototype, test it and refine it.

2. Don’t expect plug-and-play. Generative tools may make drafting an email look easy, but enterprise applications demand significant amounts of training data and time. Leaders need to adjust their expectations accordingly.

3. Invest in data quality. Data is the foundation. Organizations should classify what’s safe, semi-risky and fully restricted to avoid regulatory or security disasters. Without governance, you risk hallucinations, bias or compromised outputs. The rise of “vibe coding” disasters—where AI produces working code that looks fine but hides flaws—shows why close monitoring is crucial.

4. Establish governance and security. CXOs should directly oversee AI risk management and not just leave it to IT alone. Compliance frameworks vary by region, whether it’s GDPR in Europe or the California Consumer Privacy Act. Leaders need to be clear on things like access, storage and ethical considerations.

5. Be ready for regulation. Emerging laws will hold companies accountable for AI decisions and their downstream effects. Without the right tools for compliance, you can risk fines and reputational harm.

6. Plan for scalability. An AI solution that works well on one team’s laptops might fail when rolled out across the enterprise. Leaders need to plan for how tools grow and evolve over time.

7. Involve the workforce early. People may be the most overlooked step of all. Employees fear that automation will eliminate their jobs. In fact, AI can open opportunities for higher-value, more innovative work. But that only happens when leaders engage teams from the start and are open about what’s coming. Most successful executive use cases start with insights from employees closest to the work. Involving them early builds ownership and pride.

Moving Forward With AI

For CXOs, the mandate is clear: Embrace AI, but do it with care and intent. Don’t think of it as a magic solution. Start small, aim for low-hanging fruit first and then expand as the organization builds confidence.

I often think back to the early days of ChatGPT. In 2018, it was a novelty—good for writing limericks and not much else. Today, it shapes how professionals work and think across entire industries. The same arc will play out with AI more broadly; what seems narrow today will be indispensable tomorrow.

So, take the long view. Aim at real problems, build guardrails and remember that slow and steady wins this race.

Read the full article published by Forbes.