Should Your Company Go All-in on AI Now — or Wait It Out?

If you’re a business leader, you have an important decision awaiting you today.  Will your company invest in emerging AI technology before the dust settles in the race for AI supremacy? Or will you maintain the status quo, dabble a bit in AI and save most of your chips for when the cards are clear?

Whatever you decide, it will impact your business. But the only wrong decision today is not having a clear strategy for how you will invest in AI. This article will help you crystallize your decision.

Before we dive into the pros and cons of each direction, let’s understand the ecosystem players. The race is being contested across three categories.

First, the frontier AI labs. These are companies built with the core purpose of creating the AI infrastructure of the future. In the enterprise market, the leaders are Anthropic (Claude) and OpenAI (GPT), with Mistral and DeepSeek also making progress.

Second, the emerging businesses developing AI-native enterprise solutions. This is a growing marketplace where companies like Clay, Bland and others are playing. These plug-and-play technologies give you a rapid way to AI-ify your workflow and access a go-to-market strategy.

Lastly, there are established enterprise giants. These are the companies we already use that are creating their own AI solutions. Think of data companies like Google (Gemini) and Meta (LLaMA) that are investing in developing their own models, as well as business operations platforms trying to build orchestration layers and reasoning engines. There you find the likes of Microsoft (Copilot Studio), Salesforce (Agentforce) and ServiceNow (AI Agent Studio).

Of course, there are others in each category, but these examples are sufficient for our thought experiment.

The risks and benefits of being an early adopter

When AI solutions are implemented with solid engineering, using an approach such as my “SPI” framework, they will allow your team to revolutionize your go-to-market strategy.

If your company is full of eager and inventive people, the leverage that tools such as Claude Code allow your team to create is unprecedented. Initiatives that once required multi-disciplinary teams working for months and millions of dollars now require one or two competent people and take only a few days to achieve.

Building has never been easier or faster. This means you should invest as much time as you can afford into deciding what you truly need to build, as this is how you create a sustainable early-adopter advantage.

But it is not all rosy for the early investor. In my consulting work helping companies navigate their investments in technology like Salesforce and AI automation, I see firsthand the struggles of those adopting new AI solutions.

Salesforce has heavily promoted its AI solution, Agentforce. Yet clients of mine, who made investments in Salesforce’s native AI solutions barely a year ago, are already finding that the tools they bought are a generation behind. They are losing support and promised functionality while being asked to invest again to upgrade for the latest features.

If you choose to be an early adopter, this is something you need to expect. You are unlikely to see a return on investment from these tools. Or at least not in the same sense as you used to see from technology investments in the pre-AI era.

Rapid evolution means the technology you buy has a shelf life measured in months, not years. And all future upgrades will come at an additional cost. You are funding the bloated budgets of these AI-focused companies.

• Benefit: Build strategic tools and services to get ahead of the curve.
• Risk: Lose money by funding AI tools that do not keep up; pay to be a beta tester.

The risks and benefits of waiting for a clear market leader to emerge

Fully investing in AI today carries risks. But if you decide to wait and see which players win the AI race, what exactly are you waiting for?

That question doesn’t have a simple answer. The better question to ask is, “How do I know when I have waited long enough?”

Right now, everyone wants your money for their AI solutions. For the most part, those AI solutions have been rushed to market due to a sense of FOMO and a desire to please investors. However, the “SaaSpocalypse” shows that the rush has not all been beneficial. 

But waiting doesn’t mean you can tune out the AI news onslaught.  Instead, you must tune in to the right signals and stay informed. Invest your time and attention to understand how the technology continues to evolve, particularly in your industry.

Watch and learn how early adopters use these tools while resisting FOMO. You will know you’ve waited long enough when your whole team clearly understands where and how to leverage AI. This is when the adoption journey feels like a traditional business investment and not like a bet made from a place of desperation.

But what if you wait too long? Well, that is the main risk. If your competition finds a way to create a deeply unfavorable market dynamic by leveraging AI, you may end up in an irrecoverable situation.

Therefore, the best strategy for waiting is to encourage creative tinkering. Do you have an eager AI enthusiast on the team who is trying to get everyone to jump on the latest AI fad? Give them clear business objectives and limited budgets to play with. Let them build proofs of concept.

You don’t need to roll out new AI solutions for entire departments. You don’t need to cancel your CRM contract and vibe-code your own. You don’t need to add an “AI-native” feature to your offering.

Instead, experiment from a place of stability. Here, you are best positioned to watch and learn. To try and fail safely. And to act when the time is right! Get this right, and you stand to see a positive ROI from AI technology.

Just don’t wait too long!

• Benefit: Introduce AI tools from a more stable position.
• Risk: Wait too long and get outpaced by your competitors.

If you’re a business leader, you have an important decision awaiting you today.  Will your company invest in emerging AI technology before the dust settles in the race for AI supremacy? Or will you maintain the status quo, dabble a bit in AI and save most of your chips for when the cards are clear?

Whatever you decide, it will impact your business. But the only wrong decision today is not having a clear strategy for how you will invest in AI. This article will help you crystallize your decision.

Before we dive into the pros and cons of each direction, let’s understand the ecosystem players. The race is being contested across three categories.