AI Technology Leaders Needed

Urgency is at an All-Time High

There is no more time to wait. 85% of firms believe they have less than 18 months to build a viable AI strategy or face real business risk (Cisco, 2024). Nearly every company – 98% – feels pressure to deploy AI now (Cisco, 2024). Budgets are shifting fast: half of companies now dedicate 10-30% of IT spending to AI (Cisco, 2024). Leaders know that AI’s impact will be bigger than expected: 59% believe it will surpass forecasts within five years.

So, the urgency is clear. The money is there. The potential is massive. But so are the pitfalls.

Why AI Technology Implementation Falls Short Today

Despite huge spend, too many projects fail to deliver. BCG reports 74% of AI projects don’t hit expectations (BCG, 2024). Forrester warns that 75% of firms trying to build advanced AI systems alone will fail (Forrester, 2025). DIY approaches waste time, budget, and brand trust.

Meanwhile, famous mistakes keep hitting headlines:

• The Chicago Sun-Times published a fake reading list invented by an unchecked LLM (2025).
• McDonald’s shut down a drive-through AI pilot after it ordered 260 McNuggets by mistake (2024).
• NYC’s ‘MyCity’ chatbot told owners to break labor laws and ignore food safety (2024).

These are not minor glitches. They damage trust and cost money. They happen when the AI project is implemented without a full spectrum consideration of the issues the organizations will face. In this regard AI Technology 

It’s Not Just the AI Technology – It’s the Project

One big reason for failure? Most firms think AI technology is only about the tool. It’s not. A smart AI technology project starts with the people. It starts with bringing in AI technology expertise to consult on the outcomes. After that, backtrack to figure out what the technology should be to achieve those outcomes. It means figuring out what other dimensions are important to work out. Then approaches to align all stakeholders. It means mapping pain points carefully. It means picking the right AI model for the goal, which protects your brand.

Too many firms forget: pure LLM models alone bring risk. Large Language Models (LLM) are an exceptional class of AI technology. They are revolutionizing the world today. Yet hallucinations still happen. In fact, Gartner Maverick research identified 9 different types of hallucinations from moody to neurotic to hyperactive to unscrupulous. (Gartner 2025, G00828342)  Worse, open data sources introduce bias and toxic content into the mix. That can stain your brand overnight. To fix this, you need clear guardrails, trusted data, and a clear process.

Another missing piece? Change champions and tools. Organizations need people on every team to advocate for AI. They answer questions. They build buy-in. They push adoption. The reality is this: tech alone does nothing. People make it work.

To strengthen the hand of the advocates, simple tools like Trusted Collection systems help with change management. All change management jobs build information. So make it easy for the champions to find the right information quickly, with an internal AI technology that references all the information about that project. Give access to the advocates. And let them build adoption, with the support of answers at their fingertips. 

Drive Productivity – Not Panic

Let’s clear up a myth: AI is not about cutting jobs. Make sure that is understood by the company, executives, and most importantly the employees. Yes, some teams will use it to reduce roles. But smart leaders know AI is about more than headcount. It’s about boosting what your people can do.

Productivity gains may show up in cost savings. But often, they appear as faster delivery, higher quality, or stronger customer service. Done right, AI means you serve more clients, develop new services, and earn more trust. Today, the world is focused on the wrong angle for AI, as a human replacement. AI should not shrink a company. It should expand the boundaries of its capabilities. AI technology makes an organization sharper and more scalable.

This mindset is key. With so much fear about AI layoffs, teams need to hear the positive growth side. The goal is not to replace. The goal is to empower. Strong AI leaders explain this daily.

Think about this for a moment. If you could use AI technology to double your people’s core deliverables, this would give you a competitive advantage. Why wouldn’t you use this to hire more staff, to further increase your ability to deliver more value to your customers? If you succeed with AI Technology, the opportunity could be to expand, grow, and gain revenue. 

Be the AI Technology Leader Your Team Needs

Today’s AI market does not need more hype. It needs leadership. It needs realistic plans. It needs champions who align tech to real business pain points. It needs people who can manage expectations and show the roadmap for real adoption. 

Data proves it: firms that run AI readiness workshops and follow change management steps see 47% higher project success rates (Virtasant/Bain, 2025). Yet only 43% of employees say their company even handles change well anymore (Virtasant/Bain, 2025). That’s a gap you can close with an AI Workshop, and expert consultation.

The recipe is clear:

• Define the problem.
• Pick the right AI model.
• Secure clean, bias-free data.
• Build multi-team champions.
• Communicate the purpose often.
• Drive adoption with trust and clarity.

This is what real AI leadership looks like. And it is needed now more than ever.

Ready to Lead? Let’s Talk.

Don’t be the next headline for AI failure. Be the success story. Be the leader who guides your teams through this tech wave with confidence and purpose.

Partner with trusted AI advisors. Run a readiness workshop. Map out your real risks and big wins. Focus on people first, technology second.

The time for AI technology leaders is now. If you’re ready to lead, kama.ai is ready to help.

Let’s build your roadmap together – and get AI right, from day one.