B2B Wins #14: The utility of AI

Understanding the utility of AI is easier than ever

Paraphrasing Kara Swisher from one of last week‘s podcasts, AI is finally showing its utility.

For B2B marketers, the concept of the utility of AI is not new. We’ve been seeing little bits and pieces of useful AI over the past few years. Technologies like 6Sense, Coveo, and Monday are examples of where AI-based applications show their usefulness across the marketing spectrum.

But I suspect AI is about to enter a moment when it is no longer the realm of specialist applications. In the next 12-18 months we’re going to see AI inhabit many of the cozy niches in marketing that have been resistant to automation. And that’s going to change practically everything.

AI as a public utility | DALL-E

Let me introduce you

As we know, much of the marketing and sales funnel happens outside of our sight. Buyers seek information to help them compare and contrast our tech with that of our competitors and various substitute products without engaging the vendors. In the past, unearthing the best knowledge was usually a result of a good network, a deft hand with a search engine, or sheer luck.

As marketers, we do our best to make sure we’re in the right earned and paid spots so that our brilliance can be discovered. But what if there were a way for buyers to connect with peers who had already solved the problem? Wouldn’t that be helpful for buyers? Sure. Marketers? Maybe.

To a certain extent, a company called Lunchclub has already solved much of that problem. I use Lunchclub for networking. Their AI-powered networking technology does an uncanny job of matching people for the purpose of interesting conversations. Now imagine the same tech was put to use in matching people with similar business problems.

I’m not sure if this should be my next company or if this is something we’ll see review sites like G2 move into in the coming year but pointing the power of AI at creating communities with interests that include solving hard problems is, no doubt, in our future. The role of the marketer in those discussions remains to be seen.

What is expertise?

We often pay dearly for skills that require expertise. Credentials and complexity coupled with scarcity mean that the best folks in some fields command high rates. But what is the value of credentials and expertise in a world where AI understands and automates even the most complex processes?

If you hire a copywriter and they use an AI tool like Jasper or ChatGPT to write an article, is that what you bought? What if they don’t disclose that they’re using the tools? Is it only the results that matter? Or should you be paying for the actual expertise of the copywriter which may, arguably, not be all that?

If you’re using ChatGPT to interpret your tax situation and it ferrets out a sweet loophole, should you take it? How will you know that ChatGPT got it right? How will you know if your tax advisor has used a tool like that? Does it matter?

AI is changing the way work gets done and it seems like there are lots of scenarios where AI technology is either going to enhance or fully replace the skills of professionals. I don’t feel like it’s cheating if these professionals are using AI to augment their skills. I’m also fine if AI tech replaces some of these roles. That said, I’m definitely going to want to renegotiate my rates.

If you’re paying $750 an hour for expert legal advice, you would expect that a person is going to be doing the lion’s share of the work. If AI technology is doing the lifting, then maybe your rate should be adjusted. The same goes for a copywriter.

AI may well cause a race to the bottom of the economics of many industries where expertise in combing through complex rules, whether it’s the English language or the IRS code. That should be good for all of us in the long run. Let’s put valuable people on the hard problems.

Computers who code

Speaking of hard problems for people, computer science has historically been one of those areas.

One of the surest ways to make a buck during the past twenty years is to become a software engineer. There seemed to be no shortage of empty chairs that needed filling. Recently, big tech has been laying off folks. But that hasn’t changed the supply-demand equation much. Software engineers remain in demand. That may soon be changing.

One of the use cases that early ChatGPT users have been experimenting with is the technology’s ability to generate computer code.

Much like creating a writing prompt, you give the AI a problem and ask it to generate code to solve that problem. The output is computer code in your language of choice. Is this technology perfect right now? Nope. But is it solidly good enough that some programmers are using it to help with the software development process? Yes, it is.

Setting aside the various Terminator scenarios that could come from computers creating computer programs, what we’re going to see in the near term is a virtual elimination of low-level computer engineering jobs.

For example, if you’re someone who builds websites, platforms like Squarespace and Wix have changed your job. In the past you were writing code, today you’re configuring platforms. As these technologies evolve, even less of the design, coding, and configuration will be required to be completed by people.

Will this eliminate software engineering jobs? No. But the productivity boost that comes from computer-generated code means that fewer engineers are going to be necessary.

Implications

I could go on and cite several other examples of where generative AI technologies are going to fundamentally change the way certain professions work. And there are likely even more that we haven’t yet imagined.

So what should you be up to in this fast-changing world?

1. Embrace the change: Content creation is the place where we’re already seeing changes. Embrace it. Instead of trying to defend the art of creating content, defend the ability to rapidly discover and test the most effective content. Generative AI is a force multiplier for A/B testing.

2. Figure out the economics: Don’t leave money on the table. Early technologies will be expensive but this space is going to quickly commoditize. You may want to forgo long-term contracts because we’re doing to see power shift from the early-stage companies to the buyers very quickly.

3. Invest forward: Look to the horizon for where you should be investing the time of your people. As in the example above, creating and testing content is going to soon be the purview of machines. It changes the role of operational marketing.

ChatGPT and similar knowledge discovery technologies are demonstrating both incredible utility and stunning fragility. Given the tremendous economic value of these technologies, I suspect that the fragility problem is going to get resolved. So real change is coming. Those who prepare sooner, who adapt as the change lands, are going to get a disproportionate share of the value.