5 barriers to AI adoption: learnings from our own journey
AI’s potential positions it as the most powerful tech on the planet. The opportunities to transform customer experiences by using AI as a marketing team are endless. But it doesn’t end there.
We’ve now started to move beyond the hype. AI is not the domain of FTSE 250’s with teams of data scientists anymore. We have seen AI democratised – through platform offerings, intelligent API’s, and all the smarts embedded in SaaS/PaaS offerings making it easier for all organisations, no matter their size to access.
MarTech in particular has been prominent in landing AI into organisations, sometimes in isolated pockets, but these are fertile grounds to experiment on.
When human ingenuity and technology combine, for me that is the sweet spot and where the magic happens. Our partners do this incredibly well. A few examples that illustrate this are Marmite TasteFace, CherryBot and the EasyJet Look and Book app. Great examples for marketeers on how AI can drive audience engagement, while creating compelling brand experiences.
There is no shortage of use cases and automation scenarios across your customer’s life cycle. I would encourage you to draw these out and map them. Then pick one or two that matches your strategy so you can start using AI in your marketing strategy with relative ease. For example:
Research suggests that organisations who are on their AI journey are already outperforming other organisations by 5 percent on factors like productivity, performance, and business outcomes.
But, let’s be honest, whether it is the way your teams collaborate or the way your customers engage with you – all our expectations have been raised as to the quality of those experiences in this era of digital transformation. This is disruption!
Experimentation is fun but at some point, you need to make a strategic decision around your AI adoption journey. There have been five key learnings from how we’ve used AI as a marketing team at Microsoft that I want to share to help you build your own AI road map and strategy.
These key learnings are data, platforms, partners, skills, and commercial outcomes.
Our 5 key learnings
1. Data
Great AI needs great data, you cannot build an AI strategy without a data strategy so invest in creating one first.
Data needs to be high quality, preferably centralised, and compliant. The more data you have the smarter you can become. Your data modernisation strategy needs to not only identify the data you already have but look at gaps in your data and how you can fill it. Great data is a competitive advantage, of course the cloud is a logical destination so you can maximise the tools available to you.
2. Platforms
We are using PaaS and SaaS offerings to leverage ready-made solutions. We are a marketing team, not a dev team; I do not want my team writing bespoke code.
These ready-made solutions mean we can optimise our data and work when we need to, helping us stay agile. It also frees up time so my team can get on with the most important tasks to deliver business impact.
3. Partners
This is the most strategic choice you will make. We have chosen partners who enable secure, compliant, and accessible AI.
Choosing your partners is the most strategic decision you will make. Will they compete with you, are they culturally aligned, can they deliver securely and at the scale your business needs? Think hard about who you partner with and why. What do you want to keep in-house and where will you use partner capability?
It’s important for us not to just talk the talk, we need to walk the walk too. By making sure our partners have the same views as us, we’ll contribute to a better future for all.
4. Skills
When you deploy these tools, do you have the skills in your team to interpret their output in a commercially meaningful way? Or will you partner to deliver this?
Around 90 percent of jobs in the next two decades require digital proficiency. We’ve developed digital skills courses to help everyone in the UK re- and upskill.
We also invest in upskilling soft skills – strategic thinking, creativity, and collaboration are becoming some of the most important skills for organisations to foster. Creativity creates innovation, better development, and programming. Collaboration is vital for remote teams or big picture thinking. And when AI is crunching data and outcomes, we’ll need strategic thinking and planning to action those critical decisions.
AI has the opportunity to augment our work in many different ways. And sometimes it isn’t about who understands the code the best – it’s also about developing the correct culture, strategy, and governance. The AI Business School has a range of online modules, from the more practical how-tos to strategic guides.
5. Commercial talk, not AI hype
What are you measuring? Focus on the outcomes you want and not the tools that get you there.
When using AI in your marketing strategy, it needs to be framed for its commercial impact. More effective media buying, smart lead routing, and improved customer service are a few simple examples. Think about what you want to achieve. And remember – AI isn’t something you just turn on and leave–it should grow, adapt, and improve. The ultimate goal is to infuse this across your entire customer life cycle.
Amplifying ingenuity
When implemented correctly, AI has the power to amplify our ingenuity. By applying AI carefully, thinking about what we want to achieve, my team have been able to focus their time and energy on adding business value and innovating.
This journey isn’t something you go on alone. To truly drive change, you must bring your whole team or organisation with you. Listen to their feedback and encourage them to re- and upskill so they can prepare for the future of work.
We live in an era of digital transformation. It’s not just customers who have high expectations – it’s us and our teams as well. With the barrier to entry for AI now lower than ever, it’s never been a better time to start thinking about your AI strategy. Learn more about the state of AI across UK businesses with our deep dive, ‘Accelerating competitive advantage with AI‘.
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About the author
Paul has over 20-years’ experience in the technology sector across a variety of VP and GM roles. Most recently, Paul was appointed as CMO at Microsoft UK after running their UK SMB business and sits as a NED on the board of a SaaS start up.
His passions lie in building engaging workplace cultures, understanding how technology drives transformation, collaboration and creates compelling customer experiences.
