Enterprise AI Adoption, From the Buyer Side

I want to talk about enterprise adoption for AI tools, but not on the GTM side. As the mythical person on the buyer side.

First things first. The vast majority of sales and GTM people have spent their careers in a world that works a certain way, and in AI, what they think will work often doesn't work here.

I've been a part of AI enterprise adoption strategies that have failed, and ones that have succeeded. My role as AI Lead and Producer means I'm in charge of the AI process A to Z, but I also have to actually make client product and media with it.

Vendors often have great products. They look amazing, and they know they work. For them. But the client is king, they get the white gloves, and we only ship them what is amazing for them. Only that.

But there is a way forward.

(Note: I'll be speaking very broadly here to protect the information of the actual experiences that happened.)

1. Settle them into it

Every AI tool demos well now. I've used probably 23,047,120 different tools by now. People see the possibility, but you're dealing with two major resistance points.

First, AI tools aren't like the conventional tools we're used to, the ones that gradually grew in capability. They're often a totally different way of thinking. That requires education and time. And no one has time (but I have a solution for this).

The second problem is that resistance to AI is very, very, VERY real. It often isn't in your face, either. People see AI as a threat and fight it asymmetrically. The ways that teams and individuals undermine AI adoption are varied enough to be a science in themselves.

When I say settle them into it, what I'm saying is that the solution is to make it so people gradually get used to it all. You build a relationship and then stay in touch in a real and human way. Not just with the decision makers, but with as much of the team adopting this tech as possible. There are a number of people who are AI curious. Take the time to be a human to them and they'll see AI not as a threat to their human work, but as a way to augment it.

This eventually settles resistance, and it opens doors for self-education, or for teams taking 30 minutes here and there to use what you have and find ways to work it in themselves.

2. Legal, law, and lawyers

I was speaking to someone who leads AI at a major production company, and the biggest roadblock was lawyers. Totally true. Lawyers understand the dangers of AI, and they're often right about those dangers. So when we say roadblock, on the buyer side that blocker ain't us. It's the AI company and their product itself.

My job as a producer is full SOW and MSA compliance, and making sure our team follows every legal agreement we have with our clients. AI tools have a long history of being a problem for IP, brand assets, and other client materials. You need to go into intro meetings clean and clear in your understanding of this. Every project and deal is different, so bring case studies and examples of other companies you've navigated this process with.

Get ahead of the game. In a calm and smooth way, make sure a conversation with the legal team is set up, and make sure you hit the top three things they'll be looking out for. Once that happens, you have trust, and the other roadblocks they flag stop being question marks. They become parts of the process everyone is working through together.

So what gets through on the lawyer side?

Lawyers are our friends, there to protect us. But they also know you can overprotect and end up putting the company at a disadvantage. Understand that.

Be very assertive in your language and your conversations with them that everything will be followed contractually.

And third, show the legal team the potential. They're human beings. The wow factor of what can be done also gives them license to find a way forward. I've shown lawyers at big companies what you can actually do with these tools, and one of them told me, "I know this is the future, and we'll find a way to get there." If a critical member of a team wants to use AI for something, lawyers understand their job is to support and help navigate the process. Make sure your process follows the law.

3. Build for them

Everyone is noticing the X, LinkedIn, Instagram, TikTok, and YouTube AI demo work going out into the world. It genuinely looks amazing, and we pass some of it around internally. But when you have an agency that's successful, the client is happy, and you're winning awards, why change?

The forward deployed (fill in the blank, whatever the title is) person is very key to this process. Step 1 above ideally gets you to step 2. After step 2, then what? You build for the client. That is the step. No one is going to say no to someone building things for them on someone else's dime.

Why is this important? Most companies don't have people sitting around for chunks of time doing nothing. Labor is usually filled out to the total hours needed, and that's smart company management. Does R&D time exist? It totally does, at every company. But it's elastic, and it's hard to build momentum because of that, especially when the company is in sprint time.

Having someone embedded in the company, following all legal compliance, building trust with the team, and then actually turning the AI tools into creative, is the whole game. It may not get used for the project. But AI is excellent at finding an edge on speed, price, or quality. Somewhere in there it will have a use, and then the key members of the team will adopt that usage.

Then when one initiative succeeds, the trust you get becomes a serious bonus, and the momentum really compounds.

Some enterprise adoptions don't work. It happens. But one adoption DID work, in that it solved a very specific use case, and because of that the product stuck around. We started to use other parts of it here and there, and it became part of our workflow. The rest is history.

Where I'll stop

There's a lot to process here, and a lot more still to process.

The big takeaway I want people to have is that trust, compliance, and building are your three pillars.

But there's a fourth. Time.

Sometimes teams aren't ready. Sometimes the timing isn't right. Sometimes it takes a while for people to get used to you, or to what you made. Give yourself grace in this process.

But know this. The tools you have are good. Most AI tools have an edge in some way. Trust the product, trust the process, and hopefully some of what I wrote here can help guide you as you work toward your goals.