Marketers Can Balance Risk Aversion and Innovation When Adopting AI by Following These Strategies
How do you balance risk aversion and innovation when adopting AI?
Jon Williams shares his top take-outs from BrXnd.ai in New York with LBBonline - Little Black Book.
(A 2-minute read with a caffè macchiato and biscotti)
Founder and CEO of The Liberty Guild, Jon Williams, on how you can leverage the benefits of AI and mitigate potential risks.
I didn't just see it with my own eyes, I judged it.
The machines versus the humans. AI vs student creatives.
This all happened at The BrXnd event in New York.
It was too hard to tell the difference between the two.
Too hard. Too soon.
Once the competition had finished, we listened to some great speakers. There was one bit that really stuck with me. It was all about how marketers can balance risk aversion and innovation when adopting AI.
So here are my top take-outs.
Start small: But do start. Begin with pilot projects or limited-scale implementations to test the waters and understand the potential impact of AI on your marketing operation. This approach allows you to minimise risks while exploring innovative AI solutions.
Conduct thorough research: Before implementing any AI technology, really look under the hood and do the due dil to understand its capabilities, limitations, and potential risks. This will help you make better decisions and mitigate potential negative impacts.
Collaborate with experts: Talk to geeks. A lot. Seek guidance from AI experts, data scientists, and consultants who specialise in AI implementation in general and in marketing. Their expertise will open your eyes. Change your perspective. Help you find the right things.
Monitor and measure: Head out of the sand time. Continuously monitor the performance and outcomes of what's going on out there. Establish metrics and KPI’s to track the impact of AI on your goals. Regular evaluation allows you to assess risks and make adjustments accordingly.
Embrace a culture of learning: Give your team permission to play. Celebrante experimentation and learning from failures. Innovation always involves risks, but by pushing an intrapreneurial mindset and emphasising the value of learning, you can create a culture where you make your own success.
Ethical considerations: Don’t abdicate responsibility to the machines. Ensure that all the ethical considerations are integrated into any implementation. Keep a human in the loop. AI technologies should align with privacy regulations, data protection standards, and ethical guidelines. Don’t just throw your data into a free version of GPT.
Adapt. Adapt. Adapt: The AI landscape is constantly evolving, and new technologies and approaches emerge every week. Stay on top of it all. There is no ‘how to’ guide. Nor one single oracle of everything. Be flexible and adaptable so you can react to new opportunities while managing your risk.
Test and validate AI output: AI systems can generate inaccurate or biassed results. They are after all just a distillation of all the bias on the internet. Make sure you validate the oeuvre.. Maybe it’s human oversight, audits, or the use of external validation tools to ensure the accuracy and fairness of AI-driven marketing campaigns. But keep an eye on it.
Follow this… and get the balance right. Getting caught between the rock and hard palace of risk aversion and innovation will just slow down progress. You need to get cracking or you will miss the boat. But the good news is it’s not too late. You can leverage the benefits of AI and mitigate potential risks.
Photo by Steve Johnson on Unsplash
