The Art of Not Rushing AI Adoption
- Brainz Magazine
- 13 hours ago
- 5 min read
Written by Annette Densham, Chief Storyteller
Multi-award-winning PR specialist Annette Densham is considered the go-to for all things business storytelling, award submission writing, and assisting business leaders in establishing themselves as authorities in their field.
AI is a constant background hum, loud enough to be distracting and vague enough to be confusing, but it’s quickly become part of so many facets of our lives, even if we don’t understand it. AI adoption sits in that awkward space between curiosity and dread. We know it matters, but every option seems overhyped, half-baked, or risky in ways no one can clearly explain.
One minute, we’re being told it will transform your business. The next minute, it’s ‘danger, Will Robinson, as we’re warned it could expose a business to risk. In the midst of this noise, professional services businesses are trying to get client work out the door and not miss meetings.
No one wants to be left behind, but who wants to make a call that can’t be undone? The more talk and hype around AI makes it harder to know what a sensible next step looks like.
Adopting AI isn’t a future conversation
Inbal Rodnay spends her days inside accounting, legal, and advisory firms, helping leaders make sense of AI. A former software engineer and Head of Technology and Innovation turned AI strategist and educator, Inbal says people are confused and overwhelmed about when, where, and how they should integrate AI into their business.
“People aren’t confused because they’re behind,” Inbal says. “They’re confused because there’s so much information about AI. The problem isn’t knowing you should respond, it’s knowing how to respond without blowing time, money, or trust.”
Gartner estimates that by 2026, more than 80% of organisations will have used generative AI APIs or tools, but less than 30% will see measurable, sustained business value. A significant portion of AI spend goes to duplicate tools, overlapping licenses, short-lived experiments, and tools teams stop using after initial curiosity. That means the majority of spending sits in trying something instead of changing how work is done.
“Everyone seems to have an opinion, but very few have a calm, practical answer. That gap between what you’re seeing online and what feels realistic is completely normal.”
Be the confident majority
“Most firms aren’t innovators or early adopters. They’re in the early or late majority. AI is constantly evolving, and there’s nothing wrong with being the early majority because it means you can be more intentional about how you use AI in your business.”
Inbal calls the business that falls into this category of the AI conversation, the Confident Majority, 84% fall into this space. Inbal says this is where the most sensible decisions get made. “AI is moving fast, but that doesn’t mean you have to run. Progress isn’t about speed. It’s just as important to be clear about what you need to use, being confident as a business or a team to use, and having a timeline on when you move. Don’t be pushed into it by all the hype,” she says.
“But the answer isn’t to panic or to ignore it altogether. It also doesn’t mean you should wait it out and hope this all blows over. The goal is to engage with AI in a way that helps your business, not distracts from it.”
“Leaders feel like they should be doing something with AI, but they don’t know what that something is. They either freeze, or they grab a tool because everyone else is. That doesn’t work.”
The technology adoption curve has been studied for decades, most famously by Everett Rogers in Diffusion of Innovations, who showed the majority of organisations don’t sit at the front of the curve. Early and late majority adopters are the ones who turn technology into something stable, scalable and commercially viable.
“Innovators are supposed to experiment,” Inbal says. “They try things early, they break things, they post about it. That’s their job, but it’s not yours.”
Copying that behaviour creates stress instead of progress. “You don’t get paid to be first,” Inbal says. “You get paid to be reliable. Paying for curiosity without getting capability in return is time wasted on experimentation without clear outcomes and intent.”
More AI tools aren’t the answer, asking better questions is
The Confident Majority starts with a simple test that can be used every time a new AI idea pops up.
“Where are we on the adoption curve? Where is this capability right now? Is this a real problem, or just an annoying one?” Inbal says. “It’s ok to slow down instead of jumping into building way too early. Use what’s already in your stack first. You’re probably already using Google Workspace, Microsoft, Asana, or ClickUp. Learn how to use these intentionally. Building should be the last option, not the first.”
A big misconception is that if you’re not experimenting constantly, you’re falling behind. “That’s just not true,” Inbal says. “Experiment, absolutely, but do it on your terms. Start with small, contained, and reversible steps. This is part of the learning process. You're looking for an outcome that’s either ‘this works’ or ‘not yet’. That’s it.”
“Once you stop thinking you have to be an innovator, a lot of pressure disappears. You can watch what’s happening without feeling like you’re failing.”
Waiting vs deliberate
One of the biggest risks Inbal sees is firms misreading caution as safety. “There’s a difference between being selective and doing nothing,” she says. “AI isn’t something you can park for two years and come back hoping to catch up.”
“If you decide not to use AI, know your clients are using it. If you have a team, they’re experimenting with it, often in the shadows and on their own devices, opening you up to risk. People’s expectations about speed and service are shifting.”
McKinsey’s research on generative AI adoption reinforces this. AI tools have reset what reasonable speed looks like. If you’re not using AI, your clients are. Expectations are shifting whether you like it or not.
“If you completely opt out, you don’t stay neutral,” Rodnay says. “You fall behind in the conversation, and then you’re forced to react later under pressure. Stay curious, watch closely, learn continuously, and build understanding, even if you’re not rolling things out firm-wide yet.”
Fear is one of the biggest blockers to sensible adoption. “A lot of resistance to AI comes from not understanding it,” Inbal says. “People are either scared it will replace them, or they think it’s magic.”
Inbal’s book AI Magic: 6 Steps to AI Mastery in Your Firm is a practical guide for professionals ready to work smarter, and a must-read on your book list.
If you’re still debating how AI will or won’t work in your business, you’re not late to the party. But if you’re asking things like, how do I actually use AI in my day-to-day work without messing about, which tools are worth learning and which ones are just hype, and how do I bring AI into the business without compromising trust, quality, or time, you already know this can’t stay theoretical. The question isn’t whether AI matters. It’s how to make it practical, ethical, and sustainable in a way that works for your business.
Annette Densham, Chief Storyteller Multi-award-winning PR specialist Annette Densham is considered the go-to for all things business storytelling, award submission writing, and assisting business leaders in establishing themselves as authorities in their field. She has shared her insights into storytelling, media, and business across Australia, the UK, and the US, speaking for the Professional Speakers Association, Stevie Awards, Queensland Government, and many more. Three-time winner of the Grand Stevie Award for Women in Business, gold Stevie International Business Award, and a finalist in Australian Small Business Champion awards, Annette audaciously challenges anyone in small business to cast aside modesty, embrace their genius, and share their stories.
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