The AI Race: Why Most Companies Are Still At The Starting Line

Imagine you’re running a race where the competitors get exponentially faster as they run. 

You are. We all are. 

WTF are you talking about, Jason?

The “race” I’m referring to is the productivity race. The exponential accelerator is AI. 

Boo. I thought I was getting a Hunger Games-y tale in which bionic humans compete for the survival of their species.  

I hate to disappoint you, but the title of the post does say it’s about AI, so sorry, not sorry. As I was saying, this is about how companies that got a head start with AI are setting themselves up for exponential returns and how the companies that are getting off the line a little later can stay in the race. 

What kinds of returns?

Just two years after the release of ChatGPT, we are now seeing evidence that the companies who got off the starting line early are getting meaningful returns:

• According to IDC, the average ROI across companies that have implemented AI solutions is 3.7x, and companies classed as “AI Leaders” are seeing 10.3x ROI. 
• McKinsey’s research indicates that “players that invest in AI are seeing a revenue uplift of 3 to 15 percent and a sales ROI uplift of 10 to 20 percent.”

Within the Sales and Marketing functions, companies are seeing impressive results, in many cases from very basic implementations.

• Handshake spends 66% less time on forecasting by consolidating their data and process on a single AI-enabled system. 
• Sendoso automated outbound campaigns, resulting in $1 million in new sales pipeline.
• Mintel increased win rates by 34% through sales call transcription.
• Bloomreach more than doubled their blog output, resulting in a 40% increase in traffic from those AI-driven campaigns.
• Promega implemented a simple custom GPT that halved the time for email content creation.

So, why aren’t all companies getting this kind of traction?

Based on the various sources I’ve reviewed I would estimate that only about 30% of Marketing teams, and only 20% of Sales teams have moved past testing into implementation of AI. Staggeringly low given the kinds of returns we just reviewed. According to Salesforce research, leveraging AI is both marketers’ #1 priority and #1 challenge. Why?

The short answer is that most companies haven’t prioritized AI for their workforce. Many have allocated significant resources into building AI into their products for the benefit of their customers, but few have focused on AI solutions for enhancing their employees’ productivity.

• In another Salesforce survey, 7 in 10 marketers said their employer does not yet provide Generative AI training.
• According to IDC, the top challenge around the world is a lack of employees with the necessary skills and capabilities to utilize AI.

Teams are leaner than ever, so it’s no wonder that leaders have struggled to carve out the time to define a path to AI proficiency for themselves and their teams. This is what I like to refer to as the AI Catch-22: I know AI can save me time, but I can’t find the time to figure out how. 

The good news is that there are some strategies that leaders can employ to break themselves out of that cycle. 

Practical advice for team leaders 

Here are 5 core principles that can help leaders effectively accelerate their AI adoption:

1. Create bandwidth first. There are a number of time-saving use cases that are simple and inexpensive to implement. Start with those and start playing with house money. For example, if your salespeople spend time filling out call reports, using an AI notetaker and connecting it to your CRM is an easy way to eliminate most of that work. 
2. Focus. AI’s hype machine is overwhelming, even for the most dedicated AI believer. Don’t get distracted. Think about the specific tasks that are most time-consuming and mind-numbing and stay focused on the AI solutions to those problems.
3. Don’t worry about what solution is the absolute best. At the rate these tools are evolving, the “best” solution today is probably not going to be the best for long anyway. If a solution works for you, use it and move on to the next opportunity. This is the worst AI will ever be, so if that solution works today, it’s only going to get better. 
4. Take a human-centered approach. AI should augment human capabilities by taking on the mundane stuff humans don’t like doing. Technology adoption isn’t just about the technology itself. If the users don’t see and feel the value, they won’t use it. 
5. Create curiosity. If you can get your team excited about the possibilities, curiosity can be a force multiplier. This space is moving fast and accelerating (more on that in just a sec), so the more engaged your team is, the better off you will all be. 

Things are moving fast, so it’s time to accelerate. 

One of the most interesting aspects of AI is the idea of “recursive improvement.” Think of it like a snowball rolling downhill. Each new AI advancement helps create even better AI tools. The early models helped build more capable ones, which in turn are helping build even smarter versions. It’s not just linear progress – it’s compounding improvement. We’re still at the beginning, but you can already see the acceleration happening. It seems like every week, we see a breakthrough that would have seemed impossible just a year ago. It’s going to get even faster. That means you’ve got to be in the race. 

Start now and it’s the biggest opportunity of our lifetime. Wait too long and it’s the biggest threat. 

If this sounds overwhelming to you, drop us a line. We can help. We’ll see you out there on the track.