How to make AI less of a hot potato

Achieving AI Readiness: key principles to consider

Establish principles for AI usage

From the offset you’ll need to develop a set of ethical guiding principles to shape your approach to AI. This could include considerations around data collection & privacy, human oversight, and transparency. Meet with cross-functional colleagues from data, compliance and tech teams to bring them along the journey with you, agree on decision-making rules and add a level of governance and co-creation to your AI strategy.

For example, perhaps the goal should be to use AI to augment your team’s capabilities, not replace human judgment. Determine which tasks are best suited for automation and which require a human touch. Take a look at your customer journey, at which points do the audience benefit from human contact, (for instance dealing with sensitive personal subjects where the stakes are high), and how could AI enhance more routine areas? 

Consider the principles & benefits of AI

AI will continually evolve but it’s worth considering its fundamental principles and benefits as a useful frame of reference when considering its application to your business issues. Some of these include;

• Increasing efficiency – of regular or manual tasks so your team can be more efficient
• Accuracy – reducing human error in certain tasks
• Speed – at absorbing and analysing lots of data
• Enhancing decisions – using data and predictive analysis to enhance decision making
• Personalisation – in customer communication and offerings
• Removing bias – in dealing with data and facts only, AI circumvents the bias that human analysis can contain

The next step is to identify the specific areas where AI could drive improvements for you.

Business/Marketing pain points & opportunities

Look across your entire range of services and distribution channels to determine the most impactful ways to apply AI. Consider both your customers and your employees and make a list. At this point don’t focus too much on the solution but the key issues – what are pain points which could be improved upon? E.g. are servicing times too high, or are employees consumed with manual tasks that detract from providing their value and expertise?

Create an AI scoring matrix

List these marketing or business pain points and opportunities on one side of a matrix. Then on the other side a list of factors which should help you make a more informed decision on whether AI is well placed to provide a solution. These could include:

• The size of the particular issue / opportunity
• The likelihood of AI being able to help (based on the principles set out in section three)
• The business risk of implementation e.g. data privacy considerations
• The ease of implementation – a key factor to assess what area you initially look into
• Potential business impact if AI could help

I’d suggest giving each criteria a min and max score based on importance. For example, ease of implementation and low risk might be the key criteria to start with so you can get some quick wins on the board.

The process of mapping this out (even if you use a lot of assumptions) will help structure your decision making and priorities. It will also arm you with a considered response when stakeholders ask ‘ why aren’t we doing x or y with AI… ‘ for instance.

Evaluate which AI to use and/or partner with

Once you’ve decided on your two or three priority areas research various AI solutions to find the ones that align best with your needs. For marketers these could be to augment your products and services, aid in campaign development or just making life easier behind the scenes! For instance, you may decide that assisting your content team by speeding up the process of creating a ‘first draft’ is the way to go. So using the likes of generative AI tools ChatGPT, Claude AI and Midjourney imagery would be beneficial. It could be through the implementation of Grammarly to reduce human error in editing, or tools like HubSpot and Hootsuite to automate your campaigns.  There are 100’s of tools to choose from, take some time to think about which will be of the most benefit to your team.

Start small and iterate

Begin with a pilot program, closely monitor the results and don’t be afraid to experiment. After all, AI is still fairly new for most of us and it will take some time to establish what mix of tools are right for your business.

Define criteria for use and continually measure results

Once you’ve established guidelines for when, how and which AI should be deployed it’s important to look at  the metrics you will use to measure success –  both in terms of quantitative results and the qualitative feedback from your team and customers. Did it solve a problem? Did it lead to cost-savings? You’ll need to continually track and optimise as you refine your AI strategy.

Final Thoughts

It seems that AI comes with more questions the more you delve into it, and there’s certainly plenty more to come on this topic.  For now though, the first steps are to consider your attitudes to using it, how you can use it, and how you will govern and message it’s impact.

Get the basics right, and your marketing team could lead the way for other departments. As stated by Rob Thomas, IBM, “AI is not going to replace managers, but managers who use AI will replace the managers who do not.“

We’d love to hear how your teams are using AI for success. Why not get in touch for a chat about how your marketing department can harness AI tools?