How to Develop Corporate AI Guidelines

Reading Time: 25 minutes

How do you harness the power of AI responsibly, making sure you’re balancing innovation with ethical use?

Many companies, in their rush to adopt AI, struggle with setting clear, ethical guidelines. This can put them at risk and prevent them from truly benefiting from AI’s transformative potential. Fortunately, we’ve got someone today who can help us navigate these challenges. 

Kai Blakeborough is the Senior Research Analyst at Brotherhood Mutual Insurance Company and he’s on a mission to make AI both accessible and responsible. Kai is an expert at breaking down complex AI concepts and pinpointing strategic uses for both people and teams. He’s led AI adoption initiatives, developed important corporate guidelines, and conducted training programs to ensure AI is used to uplift and empower. Plus, he’s been a featured speaker at numerous webinars and events, sharing best practices for responsible AI use.

AI in Marketing: Unpacked host Mike Allton asked Kai Blakeborough about:

✨ Key Components: Learn the essential elements needed to create comprehensive corporate AI guidelines for responsible and ethical AI use.

✨ Effective Implementation: Discover practical steps and strategies for developing and implementing AI guidelines, including overcoming common challenges.

✨ Training Importance: Understand the significance of training programs in promoting responsible AI use and fostering an empowering AI mindset within teams.

Learn more about Kai Blakeborough

Resources & Brands mentioned in this episode

Full Transcript

(lightly edited)

Guiding the Future: How to Develop Corporate AI Guidelines with Kai Blakeborough

[00:00:00] KAI Blakeborough: My vision for using AI kind of rests on three bedrock principles. The first one is people over processes. And I say that because knowing that AI is going to have a transformative impact on society, it starts with teaching our people to use it well, teaching our teams and our communities to be able to leverage these technologies for their own betterment.

Uh, the second one is augmented over automated. I believe in humans in the loop, humans being a central part of decision making. And that, especially at this stage that we take a role and a perspective towards deploying AI that helps people work better, you know, find new efficiencies, but elevate their capabilities by being boosted by the capabilities of AI and finally safe over snazzy. Deploying systems that protect user data, protect customer data.

So that we can give our teams confidence that they can do their best work within these systems without risk of it getting jeopardized. So that’s why I’m glad to have this conversation today, because we’ve got a lot of influential people who are listening to this and a lot of decision makers, and also a lot of enthusiasts.

And hoping that they can pick up a little bit so that they can be confident that they’re moving forward responsibly in their own paths.

[00:01:24] Mike Allton: Welcome to AI in Marketing: Unpacked, where we simplify AI for impactful marketing. I’m your host, Mike Allton here to guide you through the world of artificial intelligence and its transformative impact on marketing strategies. Each episode will break down AI concepts into manageable insights and explore practical applications that can supercharge your marketing efforts.

Whether you’re an experienced marketer just starting to explore the potential of AI, this podcast will equip you with the knowledge and tools you need to succeed. So tune in and let’s unlock the power of AI together.

Greetings program. Welcome back to AI in Marketing: Unpacked where I selfishly use this time to pick the brains of experts at keeping up with and integrating or layering artificial intelligence into social media, content, advertising, search, and other areas of digital marketing. And you get to learn to subscribe to be shown how to prepare yourself and your brand for this AI revolution and come out ahead.

Now, listen, there’s something many of us have been wondering. How do you harness the power of AI responsibly, making sure you’re balancing innovation with ethical use. Many companies in their rush to adopt AI struggle with setting clear ethical guidelines. This can put them at risk and prevent them from truly benefiting from AI’s transformative potential.

Fortunately, we’ve got someone today who can help us navigate these challenges. Kai Blakeborough is the senior research analyst at brotherhood mutual insurance company. And he’s on a mission to make AI both accessible and responsible. Kai is an expert at breaking down complex AI concepts and pinpointing strategic uses for both people and teams.

He’s led AI adoption initiatives, developed important corporate guidelines and conducted training programs to ensure AI is used to uplift and and empower. Plus he’s been a featured speaker at numerous webinars and events, sharing best practices for responsible AI use. Hey, Kai, welcome to the show.

[00:03:19] Kai Blakeborough: Hey, thanks for having me on Mike.

I’m excited to have this conversation.

[00:03:24] Mike Allton: Me too. I’m so glad to have you. This is a really important conversation. We’ve only touched on this a little bit briefly in a previous conversation with Mitch Jackson, the streaming lawyer, and that was really focused on copyright and IP issues. And we’re going to be talking about all kinds of other ethical aspects of AI, but if you could start by just telling us a bit more about your journey and how you became, let’s just say passionate about responsible AI use.[00:03:48] Kai Blakeborough: Yeah, I’d love to. So AI particularly ChatGPT was a big part of changing my career trajectory. You know, back when AI was ChatGPT was launched in December, 2022.

It was a wake up call for me because I, I don’t have a technical background. I have a background in nonprofit communications and and a little bit in the legal space as well. And so when I finally saw a chat GBT released to the public, it was my signal that, Oh, there’s something here and you don’t have to have a technical background to make the most of it.

But also along with it something it there being something there, there was something that where I needed to realize that, wow, this has a huge transformative potential to change our society. Either for good or for harm, and I’ve realized that as we look forward to ai, you know, I, I think about it this way, Mike, there, many of us who are millennials, grew up with internet secondhand for the first time.

The generations before millennials didn’t really know what it was like to have internet access from the moment we were when we were kids. Then when we look at Gen Z. They grew up with social media secondhand. They didn’t know world without it. And this next generation to come, Gen Alpha, it’s going to be the same way with generative AI.

I think anybody listening into this podcast knows that it has the potential to transform the way that we work. And the way that we can complete tasks and the way that we can connect knowledge. And so I see this, and this is already happening, but becoming a more ubiquitous part of our society and of our everyday lives.

And so if we thinking about how we didn’t really get it right with social media, social media has caused as many problems as it’s solved. And now we have a chance to fix how we deploy a game changing and immersive technology for the next generation. And so the reason why it matters that we’re talking about it now, and this is something I really realized very early on in my journey is that the seeds we plant today into how we use AI.

Will bloom into how the next generation experiences it in their everyday life because it’s going to be an embedded into society by the time they become adults. And so that matters not just for my kids, but for their kids and, and for our future communities and societies, the way we use AI today matters.

And we have an opportunity to set the tone. Even just as users of AI and as leaders who are figuring out, figuring out how to deploy AI in order how to do that responsibly. So the, my vision for using AI kind of rests on three bedrock principles. The first one is people over processes. And I say that because Knowing that AI is going to have a transformative impact on society, it starts with teaching our people to use it well, teaching our teams and our communities to be able to leverage these technologies for their own betterment.

The second one is augmented over automated. I believe in humans in the loop humans being a central part of decision making, and that especially at this stage that we take a role and a perspective towards deploying AI that helps people work better. You know, find new efficiencies, but elevate their capabilities by being boosted by the capabilities of AI.

And finally safe over snazzy deploying systems that protect user data, protect customer data so that we can give our team’s confidence that they can do their best work within these systems without risk of it getting jeopardized. So that’s why I’m glad to have this conversation today, because We’ve got a lot of influential people who are listening to this and a lot of decision makers and also a lot of enthusiasts.

And hoping that they can pick up a little bit so that they can be confident that they’re moving forward responsibly in their own paths.

[00:08:21] Mike Allton: I don’t know about all of you listening at home, but I was just nodding my head the entire time, Kai, that you were talking. To start off, your Kind of eye opening moment with a I was very similar to mine.

That’s why I’ve started this podcast. I came to this realization last year that a I is going to have this transformative effect not only on all society, but on myself, my colleagues in the marketing space. And I felt like I was behind from the start and I wanted to change that. And I know many of my colleagues are feeling that same way.

So that’s why we started the podcast. And then I continued nod my head as you were talking about how we are At this point where we have an opportunity to positively impact how our children and our children’s children adopt these kinds of new technologies. And unlike social media, unlike so many other technologies in the past.

And then my heart was just singing when you were using alliteration throughout your description of your principles, those were fantastic, but we’re going to talk specifically about corporate guidelines and how corporations, so many of you, like you said, are, are decision makers and, and key marketers in your organizations.

And we want to help you with that. So what are some of those key components that organizations might want to consider if they want to develop some guidelines for how they’re adopting and implementing AI internally?

[00:09:40] Kai Blakeborough: Yeah, well. I think it’s important to start off by saying that a lot of times we think of guidelines as procedural or formality, but in reality, they’re anything but I was just looking over a Deloitte report from just this last quarter.

Even as of June, there are only 23% of people who rated their organizations as highly prepared for the challenges of generative ai. And a good friend of mine once told me that guidelines were like brakes on a car, guidelines, and I should say, and a good governance effort because a lack of breaks is what holds you back from performing at your full speed.

Because if you don’t have breaks, you don’t have a way to stop. So getting these in place sooner rather than later puts you ahead of the curve, makes you one of the 23 percent who is prepared for the challenges and not the mental math, 77, 77 percent who aren’t. So I, I encourage organizations to kind of take three big pillars as Foundations for their corporate A.

I. guidelines. Number one is tools. So hopefully your teams are doing a part taking the role of identifying and vetting A. I. tools, and ultimately creating a safe environment in which your employees can work with your business data without fear of data leakage or prompts being used to retrain models, anything like that.

That’s a well known fear. It’s easily overcome if you vet tools that your employees can use. In your workplace. And once you identify those tools, then it’s about explaining how they should or should not use those tools appropriately. You want to ensure that those usage align with your company values with company missions.

And also that you’re thinking through the unique uses that your teams might have with these AI tools. So recently I was doing a training and I asked people to raise their hands. And say how many of you have tried generative AI by now? And of course, a hundred percent raised their hands.

There wasn’t a hand in the room that hadn’t at least tinkered with chat GBT or whatever tool they wanted to try. But when I said, how many of you uploaded a photo to generative ai, only two people in the entire room raise their hands. That’s critical to think about as we think about corporate AI guidelines, because it’s not just text generation.

Now I will say there weren’t a lot of marketing people in that room, so that might be why there was such a little percentage, but of course there are different risks with image, with video, with audio, and. If you’re sending out guidelines, you need to think about how to safeguard your teams and your company from the risks of each of those modes of those these multimodal tools that are coming out.

So saying how you can and how you can’t and how you can protect yourself is really important. And then, of course, in addition with the tools and usage, you want to let people know what governance framework you have in place. Thanks. And what their role is within that governance framework. So one of the things that we’ve talked about is informing your manager when you’ve produced something that has been aided by AI, especially if it’s going to be consumed by customers so that there can be that extra level of scrutiny to make sure that everything’s there, everything’s correct.

Of course, also you have the, the duty of every employee is to take responsibility for their own output and to verify. Information that they’re relying upon factually. So getting into those duties that your team will carry out and also what you expect of employees and managers and other stakeholders to make sure that the guidelines are enforced consistently.

[00:13:51] Mike Allton: Those are huge points. And again, I’m going to reference that that previous episode we did with Mitch Jackson, folks, I’ll link to that in the show notes, because if you’re a marketing agency and you’re creating content on behalf of clients, there’s some really critical considerations and usage guidelines that you need to have in place so that you’re not generating entire eBooks using ChatGPT and passing them off to clients to use as though the generation that’s going to cause problems, folks, I guarantee you.

But can you walk us, Kai? it through the process of developing these kinds of guidelines. If I’m an organization, I have nothing in place today, but I want to have some things because I know at least anecdotally, some of my employees have used ChatGPT. Maybe I’ve seen some expense reports that they’re paying for it, but we don’t have anything in place as a company.

Where would we start?

[00:14:41] Kai Blakeborough: Yeah, I think. You really want to start with those foundational principles that we talked about, because once you think about tools, appropriate uses, and how are we going to enforce this policy? That really lays the groundwork for creating those guidelines. And, and I think a big part of that process is asking the right questions and, and really thinking about it from both sides of the coins, from an opportunistic and a safe.

So thinking through questions like how do we think a I could help us advance our mission? Not just and then how can I not just help us save time but add value to our clients and to our customers? What do ideal and poor uses of a I look like? What obligations do we owe our clients? Who we’re serving, what regulatory requirements might apply to our industry that that might be especially important for those of your audience who works in like a health field or insurance field, financial field or service, those type of clients.

So asking those questions and getting that information is key. And then contextualizing those, as we talked about earlier, to Understand that those look different based on the tools that are being used. So if, if you’re using audio generation or video generation tools, and there’s people involved that you want to make sure that you have their consent to produce something in their likeness, obviously that that’s one Oh one.

And considering whether you want to advise your team to watermark it. Or a caption that things are AI generated. I, Mike, I bet there that the other speaker that you mentioned also had some thoughts on that as well, but ultimately it’s a conversation that needs to involve leadership and needs to make sure that it starts from purpose.

And goes into those foundational principles and lets everything else grow up from there.

[00:16:48] Mike Allton: Love that approach. That, that too is something we’ve, we’ve touched on on previous episodes, thinking about what it is that you want to accomplish ultimately, and then deciding when, or even if AI can be applicable and helpful to that, that destination, it may not be the best route that you could go.

And if we’re thinking about that, that means we’re kind of thinking about the practicality of, of using AI. And I want to talk about the practicality of. Guidelines. How do we make sure that they’re practical, but also at the same time, adaptable, because as we both know, AI is constantly changing. We’ve already mentioned several different tools in this column, we’re only 15 minutes in.

There’s a lot that’s happening. How do we ensure that those guidelines can be useful beyond just today?

[00:17:33] Kai Blakeborough: Well, a lot of times when people think about policies, they think about something that can be made and then kind of put on a shelf for a couple of years and revisit it every three, four or five years.

And I think you just have to go in and set the expectation that generative AI guidelines, at least for the next five years are probably not going to be like that there, you need to find that balance between allowing them to be fluid. But also building on those big rocks, because there are a lot of principles that go into ethical and responsible AI usage that are tool agnostic.

So the same way that an agentic AI, which we can touch on that a little bit later, but an AI that can figure out what to do on its own and do it versus today where we have to go step by step with the AI and, and get individual results. The ethical principles that undergird how to use those tools responsibly aren’t really that different.

It’s still taking responsibility for AI generated content. It’s still keeping the human in the loop and monitoring putting humans in the driver’s seat for decision making it’s still protecting company data. Getting consent for people who’s be likeness are being used in a I like we can go back and and and apply those same principles agnostic Lee to future tools and future deployment.

So there are some house that are going to change over time and it would. I would recommend everybody to try to engage in some forward thinking and some study to see what they see coming down on the pipeline. And again, we can talk about that more in a little bit, but the core of the foundation of what you expect from your employees.

shouldn’t change.

[00:19:31] Mike Allton: I really appreciate you laying that out because it really is a shift in mindset. We’re not trying to predict the future from five, 10, 15 years from now, we’re doing the best we can to create some guidelines based on what we know today. And those can be. Change. We’re not talking about amendments to the constitution that require an act of Congress to push through.

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With your audience, don’t just market market smarter with Magai. Tap the link in the show notes. So Kai, we are crafting guidelines and trying to build, you know, good, healthy policies in the company. I’m imagining it’s not enough to just post it to the corporate Slack channel or in a Slite document someplace.

We’ve got to do some training, right? What role do you think training plays when we want to have that successful implementation of corporate AI guidelines?

[00:21:40] Kai Blakeborough: Yeah, I’m glad you brought that up. Really, without training, there’s no compliance, and you end up putting your organization at risk as well, because how can your employees be expected to follow a policy in which they’re not taught how to follow it?

So that, that’s really not a safe place to be, especially from a risk management standpoint. So training is essential. Let’s make that clear. And I think there’s A certain level of training that’s required to, you know, anybody who’s given the keys to use a I tools given a license to use a I tools.

Should be trained on the policy. And, and there’s, as I’ve looked at AI adoption and training, I’ve realized that it all starts with building off the policy and helping people understand right from the beginning, how can you use it, how can’t you use it and giving them a chance to test things in a secure environment we, we did some training in our organizations last summer where we went around to every department and we said, Let’s just do some exploration.

We’re first. We’re going to tell you how you can and can’t use it. Then we’re going to carve out some time for you to start testing these tools. And figure out what the potential is among your team and among your department. And it was that combination of testing time and training time on the policies that was key.

And we, we did go throughout the company and people, I think people said they were like 200 percent more comfortable with using AI tools after that training was complete. Then before they started using them. So that was a big win, but even then the training ends up becoming as much of a risk management technique as a adoption technique.

And I found, you know, there, You can look at a bell curve of AI adopters and see that the early adopters and the visionaries on the front end of the bell curve are pretty well equipped to find effective uses in their own workflow. But for those who are lagging along and aren’t necessarily at the front end of adopting new technology, finding those opportunities are a lot harder.

And so really when you’re investing in training, it’s not just from a defensive risk management posture where you’re teaching people how to use it right to protect your teams and your organization and ultimately the people you serve, but you’re also unlocking opportunities for them to discover efficiencies.

So you, if you don’t set up those training and discovery opportunities. You’re not going to see the benefits realized on your team. And even the best, most innovative uses or tools that you could imagine are just going to sit on the shelf and collect dust. So it’s really more than just for sake of implementing guidelines, although that’s foundational, it’s also for helping your team realize the benefits of using AI.

And I, and I found that those training moments. Often come in small group conversations where people can see what’s in front of them and see what you do with what’s in front of them. And it’s then that the light bulb turns on and they finally realize their potential in their own context. So yeah, training couldn’t be more important as our teams look to adopt AI in the next few years.

[00:25:23] Mike Allton: I couldn’t agree more with how you you’ve laid this out. It’s something that we talk about a lot, actually, on the show, even on my social media channels, about how it’s so important to have use cases, examples, how do we use AI? What kinds of prompts do we have and that sort of thing? Because it’s not. It’s own tool.

This isn’t Canva where, you know, going into it, I’m going to use this to create graphical assets of some kind as Robert Rose put it, it’s more like electricity where it’s just part of everything. He was talking about it from this perspective of how it’s, it’s silly to have an AI strategy, the same way it would be silly to have an electricity strategy.

It’s just part of everything that you’re doing to accomplish what you need to do as a business. And you’re going to figure out which AI tools, which electrical tools or so on you can import. And I love this example that you’ve given about how you use training at Brotherhood Mutual Insurance. Could you share a little bit more about how that has In turn, resulted in some positive outcomes, whether it’s at your organization or maybe others that you’ve seen.

[00:26:23] Kai Blakeborough: Yeah, I, I’ll, I’ll share a couple of examples. I, and as I do, I think that one of the principal benefits of AI is connecting people to knowledge. I, I, I really think that any employer any team leader, one of the first questions they should be asking about how to use AI is, how do you use AI? How can I empower my employees with knowledge?

They currently have difficulty axes accessing or don’t know how to access, or maybe there’s some wisdom hidden in the minds of a few seasoned employees that just isn’t is siloed off from everybody else. And so both in my personal work and in my work at brotherhood, I’ve really championed use cases that accomplish that core objective is to connect people to knowledge. So we one of the ways that I’ve done that personally is by creating a custom GPT for job seekers. It’s it’s a career coach, a career advisory board, because I’ve found that one of the best practices for AI. Is to bring in multiple perspectives to the conversation.

And so how this GPT is designed is that you can upload details from your resume, from your LinkedIn profile, from kind of your career highlights or anything that makes you, you. And the GPT will ask a couple of questions. And then you can have an advisory board that says anything from, Hey, I need to write a LinkedIn post for this audience to increase my thought leadership, or give me ideas for a podcast to start, or help me write an email to my boss about future growth opportunities, or even searching for a new job.

So. That’s kind of the concept of uploading knowledge about you that you can then draw from to get hyper tailored answers based on your own journey. And we’ve been able to do something similar to that within my organization where I, the organization that I work for has been around for over a hundred years, it’s a legacy company.

And so there’s lots of deeply held wisdom. About how best to serve our policy holders. So we were able to in an internal deployment, make some of that knowledge available to our employees. So we break down those silos and we give people knowledge to the knowledge that they need to thrive and what lots of studies have shown not just our organization is that when you can connect people to knowledge, it helps people do their work faster. It helps them discover new insights, but also it boosts the performance level of those low performers. So it’s really a win across the board and creates a culture of continuous improvement for your team.

So that’s why we’ve heard a lot of gratitude for it. Those use cases being made available, and I would encourage anybody out there who’s listening and who’s leading a team to really be thinking about that question about how can we connect our teams to knowledge more rapidly.

[00:29:28] Mike Allton: That is a great use case.

That’s exactly what we’re doing at Agorapulse. I’m leading a team where we’re building a repository for our sales team of all of our customer stories and comparison assets and everything else so that the sales team members, they’ll just be able to go into a Slack channel and ask the bot for, you know, do you have a comparison of our tool versus another tool or, you know, someone who switched and it’s just gonna be so much easier for them to service the information.

[00:29:55] Kai Blakeborough: What I love about that too, Mike, is that it puts it right where they need it to be.[00:30:00] Mike Allton: Yeah.[00:30:00] Kai Blakeborough: It’s right at the touch of their fingers. So they can just open Slack and get instant access. They don’t have to jump through a bunch of hoops. They just have it right there ready for them.[00:30:09] Mike Allton: Right, right. So what are some challenges that you’re seeing again, whether in your organization or some of the ones that you’re working with when it comes to trying to implement AI and have these kinds of corporate guidelines in place?[00:30:21] Kai Blakeborough: Well, one I touched on earlier is that people don’t feel like they’re ready. They don’t feel like they’re ready to face the challenges. I think that’s why putting these guidelines in place is so important because it gives you that North star and that foundation from which to pursue AI opportunities responsibly.

But another one is just realizing that there are a wide variety of opinions of leadership, and some of them might be buying into the hype too much, but a lot of them probably aren’t buying into the potential enough. And I, I’ve shared with our team that it’s a mistake to think about the present capabilities of AI without thinking about the future capabilities.

They, but they need to be viewed on both sides of the coin because some people in leadership maybe your listeners have experiences with their leadership that they’ve tried a couple of times and it really didn’t help them. And they really don’t understand what all the fuss is about. And others really have unlocked that benefit, but there, there’s a lot of need to really lead up and to get people on board.

With the opportunities of AI and that overcoming that skepticism is a big barrier that people who are pioneering in this space have probably already encountered and need to be prepared to if they haven’t already. I also think it’s important to just buy that, get that continuous leadership buy in as we move beyond the Proofs of concept and the pilots and go into the long term adoption and integration.

[00:32:10] Mike Allton: Could you say a little bit more about how important leadership it is? Not, not just him getting it started and implementing, but having this, this culture of responsible AI use. Cause I think it goes beyond simply telling me this is how you can use AI. It’s how you shouldn’t use AI because as we’ve already talked about, it’s not just a tool, right?

It’s something that’s pervasive. It’s there are AI tools, but there are also AI features built into pretty much every tool that we’re using, particularly in marketing today. It’s like every tool has AI in some respect. And I think it’s kind of important for individual employees to understand how to be responsible with AI.

And so I’m, I’m wondering how important leadership is in that perspective.

[00:32:54] Kai Blakeborough: Oh, yeah, it’s it’s critical, Mike. I don’t think you could overstate that because it’s not just about the decisions they make in terms of how to integrate a I, but it’s how leaderships have leaders have that immense gift. In connecting things to the why, and that’s so important when it comes to AI implementation and AI adoption.

You know, there, there’s a lot of fears among employees about what effect AI will have on their teams, on how they work on the future of work and how it impacts our society. So to have leadership come out and say, this is how we want to integrate AI. And this is why. It helps the employees feel more validated in terms of their place on the team and their, how they are valued for the work that they produce and how, what I would advocate for is that AI helps empower the employees to do more and increase their capability.

If, if leadership comes out and sets that type of vision, it’s going to make all the difference in AI adoption. And it also shows that it’s more than just a fad. It’s something that we’re pursuing intentionally. And that we’re pursuing responsibly and that we’re pursuing in the best interest, not only of our company, but of those we serve.

So the, the posture that you adapt with your employees matters and leadership buy in sets the tone, not just for what or how much, but for why.

[00:34:43] Mike Allton: I appreciate you sharing that because I know many of the folks listening to this are not the leader and they’re struggling perhaps to get their leader to take the kind of initiative and direction and, and just overall leadership that you’re describing right now.

In fact, For those of you listening, I’m going to make what Kai just said kind of available as a YouTube short so that you can share that not this part where I’m really calling that leader out, but share that little segment where, where Kai is talking about how much creating that kind of a culture in the organization empowers the individual employees.

That’s the kind of language. Thank you for sharing that that I think will resonate with CEOs and VPs of marketing and so on, who are in a position to implement these kinds of things that we’re talking about today. So looking ahead. Kai, I’m wondering how you see the future of AI guidelines evolving.

And if there are any final advice you might share about how they could stay ahead of the curve.

[00:35:43] Kai Blakeborough: Yeah, well, there’s no question that AI is going to evolve significantly. And if you want a proof of that, just look back to December, 2022. And those of us who were early users of ChatGPT three 3. 0 can look back now, compare it to our uses of GPT 4. 0 and Claude 3. 5 and realize that it’s night and day. So if that happened in 18 to 20 months. Then what’s going to happen in the next 18 to 20 months and 3 years and 5 years and I, I’ve heard some speakers say about a few things that are coming down the pipeline. 1 that we’ve talked about is the multimodal capabilities and so the ability to have a model that can interpret images coming in from your clients, videos coming in from your clients audio as well, and then obviously produce those things that marketing tools are at the forefront of those innovations, but they’re going to quickly trickle down into other industries and other domains and the innovation is going to continue taking off in that sector.

Another one is, Compute being faster and cheaper and ultimately getting smaller models that can fit on our phones and our devices and even connected devices like Internet of Things. So I’m I’m a big iPhone fan and Apple fan and I am doing this podcast from a Mac book. But one thing that I’m really excited to see how Apple is going to take it is their Apple intelligence that’s coming to the iPhones this fall, this winter, somewhere around then.

And, and that’s going to be the real bellwether of realizing that things are going to be on device. And for people who are making guidelines, that’s important because when something’s on someone’s phone, it’s going to be really hard to stop. So having those guidelines in place about how they should interact with those tools how it’d be better if they used your recommended tools and where the data would be protected, all of those things are going to be important to keep into account.

And then of course, there’s going to be agentic AI deployments where, as I said earlier, Those deployments will be able to take a task that you enter in, take multiple steps based on the guidelines that you’ve set out, and then put together something that is better than GPT 4. 0 quality. And hopefully all under a human supervision.

That’s, that’s what I would certainly advise for that, but it’s just going to be getting faster and better. And at the, at the same time, what’s not going to change. And this is the final advice I’d give for anybody listening. Is that where your organization is going to get its value is ultimately from your employees and your unique knowledge and insights and vision.

No matter how AI is going to grow, that’s going to change. AI is a means that you can use to innovate in how you carry out. Your goals and your vision and your mission, but it never should become the main thing. Because once you rely on a I to do something that your employees can currently do somebody else is going to be able to do that too.

So my advice is to keep the main thing. The main thing. Let a I propel you as you unlock new ways. To achieve new results for your company and I can’t wait to see the innovation that unfolds

[00:39:29] Mike Allton: Terrific advice and to your point things are changing rapidly. We’re recording this in august 2024. So whenever you’re listening to this Everything we’ve said has already changed For those of you listening if it’s a couple months later, you know ChatGPT5 oh might have come out by now certainly we’ll be becoming more prevalent. And so the one thing that I’ll, I’ll share that I’ve, I’ve often said is that on this particular show, we don’t talk a lot about what’s the latest and greatest in an AI, because we don’t publish enough to really keep up with that.

So I tell folks, follow the artificial intelligence show, Paul Razor, Mike Caputo, the marketing AI Institute. They do an amazing job of keeping us up to date every single week with what’s In artificial intelligence and how the various models are coming out with new versions and what that means to us, not just as marketers, but as business folks.

And one of the things that I’d add to what you just said, Kai, is we didn’t really talk about who in the organization is responsible for these things. And I’ve often said it, it should be at a committee, a council and AI council by the organization that’s responsible for that. So not everybody in the organization needs to follow this podcast or the artificial intelligence show.

Just a couple of people, one person that who’s keeping up with what’s happening in AI and has that mindset of, okay, this new feature, this new development, this new enhancement is coming out. Does that have any impact on our guidelines? That should be the question. And then we can have that committee meeting to talk about it.

Great point. Thank you. Thank you so much guy. This has been absolutely amazing. We’ve done a real deep dive and I appreciate your time for folks who want to know more. Maybe have you come in and do some additional work with their company. Where can they go and reach out or connect with you?

[00:41:12] Kai Blakeborough: Oh, I’m I’m on LinkedIn.

I’d love to connect with anybody listening and and help them discover new solutions for their teams and how to do so responsibly. So Yeah. Look me up. I’m Kai Blakeborough, I think I’m the only Kai Blakeborough on LinkedIn, so it won’t be too hard to find me.

[00:41:30] Mike Allton: Awesome. We’ll have Kai’s LinkedIn link and everything else in the show notes.

That’s all we’ve got for today, friends. Thank you so much for listening. Thank you, Kai, for joining us. Don’t forget to follow the AI in Marketing: Unpacked podcast on Apple and leave us a review. Cause I’d love to know what you think about the show, what else you’re struggling with, what else we can cover in future episodes until then.

Welcome. Thanks for joining us on AI in Marketing: Unpacked. I hope today’s episode has inspired you and given you actionable insights to integrate AI into your marketing strategies. If you enjoyed the show, please subscribe on your favorite podcast platform and consider leaving a review. We’d love to hear your thoughts and answer any questions you might have.

Don’t forget to join us next time as we continue to simplify AI and help you make a real impact in your marketing efforts until then keep innovating and see just how far AI can take you. Thank you for listening and have a fantastic day.

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