It’s only a matter of time before the CEO asks for an AI strategy. Atomic 212° Chief Digital Officer, James Dixon, has a template for marketers, focusing on what adds value, avoiding the rabbit holes of hype, hiving off the stuff IT will never allow – and some quick wins that could be fun either way.

  • AI is all the buzz in 2023, with hundreds of applications and tools having already surfaced, and more will emerge in the coming months.
  • However, this volume could prove a distraction to core marketing practices.
  • AI is some five years off from becoming a productive force against marketing pillars, so how do you separate the wheat from the chaff?

Artificial intelligence (AI) is set to be the ‘it’ acronym of 2023. After years of sitting on the edge of broad appeal, the public launch of ChatGPT in late 2022 catapulted AI into the mainstream and a proliferation of tools and use cases will come forward in the coming months.

In a recent blog post, technology investment firm Base10 listed over 200 generative AI tools across 20 use cases – and given the company called it “a condensed market map”, it’s hardly an exhaustive list of everything on the market.

These options present a veritable feast for a keen, young marketer, but also a potential threat to that same marketer’s day job as the process of trial, excitement and adoption are progressed.


But we have been here before.

As of 2020, Chiefmartec had published a list of some 8,000 martech companies, each with their respective tools and gadgets, for a marketing team to consider.


There has never been a shortage of shiny new toys for the modern marketer to play with – or simply be distracted by.

The challenge becomes seeing the wood for the trees. In a sea of tech promise, and now with AI tech in the mix, how does a marketing team focus on utilising AI for competitive advantage and not lose time and resource to the AI hype train.

Here are some suggested ways through the hype, a playbook that should keep the team curious, motivated and realistic about the fast-evolving AI landscape.

1: Be wary of the Hype Cycle

In late 2022, Gartner published the Hype Cycle for Artificial Intelligence, which outlines where various AI innovations sit across five stages:

  1. Innovation trigger
  2. Peak of inflated expectations
  3. Trough of disillusionment
  4. Slope of enlightenment
  5. Plateau of productivity

The cycle as provided by Gartner provides a reality check, with most AI tools currently situated in the aptly named ‘peak of inflated expectation’ or moving into the ‘trough of disillusionment’.

Not many of these innovations will make it through to the ‘plateau of productivity’, and that timeline is two to five years away.

It’s not that we’re being sold snake oil, simply that things take time. Don’t hold out hope of a single piece of AI coming along and transforming the way we work overnight.

2: Prepare for the CEO question

It is only a matter of time before the CEO requests an AI strategy from the marketing department.

The CEO will likely be in the ‘peak of inflated expectations’ stage and have ambitions that AI can reduce headcount, improve product and increase sales.

So we need to thread the needle, managing expectations on a realistic timeline while still maintaining an optimistic outlook about AI – and therefore allowing for the time and budget required to allow this optimism to become reality.

The holding reply should be along the lines of, “We have listed key AI tools that appear to add value to core process, these are being reviewed against a balanced scorecard of potential value, effort to utilise and scalability.”

3: Develop a long list and assessment framework

With the CEO showing interest, it’s time to action your reply to them and start assessing key AI tools.

But before filling your boots with new AI opportunities, demand a business case from yourself or the team, documenting the various tools in market (the aforementioned Base10 post can help) and how the business anticipates the likelihood a given AI tool will:

  • Add real value
  • See its benefit outweigh the cost
  • Make it to the ‘plateau of productivity’

The value equation is the curious one. For example, ChatGPT can write ad copy for digital assets, or create images for those ads, replacing a human task with an automated one. On the surface, this saves time, but that short-term time saving might not pay off with the performance of those AI ads against more crafted, differentiated ads derived and developed from human insight.

Always be mindful of efficiency vs efficacy, which is a balancing act AI is a way away from perfecting.

4: Prioritise

Once a long list of AI tools is assembled, prioritise them into testing buckets as follows:

A: Could add significant value to product, process, price or promotion

B: Could have some value to product, process, price or promotion

C: Just for fun

D: Ones IT will never allow, e.g. they require personal identifying information data to perform and the security of that data is not clear.

While the tools that fall into A and B may seem like the only ones worth pursuing, there are quick wins to be found in the ‘Just for fun’ camp.

A few ‘fun’ ones I’d recommend investigating include AI video creation platform Synthesia, which can create sales videos from text prompts; DALL·E 2 – by OpenAI, the company behind ChatGPT – which “can create realistic images and art from a description in natural language”; as well as face-swap app Reface, which has been around a number of years and you may have already playad with, but is well worth revisiting as its capabilities continue to improve.

5: Test

You have IT clearance, you have a curious CEO and an excited team, you have an assessment framework – you are good to go!

There is much fun to be had exploring this new world.

I have no doubt that we are seeing the beginning of a profound era, and despite the hype cycle, marketing practice will be enhanced by some core tools that will surface in the next two to three years.

We will be able to tell our successors that we were there in the ‘peak of Inflated expectation’, through the ‘trough of disillusionment’ and that our testing helped bring the world to a ‘plateau of productivity’ from this emerging technology.

Article originally published on Mi3.