We have lost our way
Since I believe this is going to steer a lot of debate and discussions, let me explain myself. Philosophically speaking, as marketers, do we throw money to solve problems or do we get our hands dirty to fix the problems? The difference in these mindsets is what I would like to explore.
The impending takeover of our jobs by AI makes this even more time sensitive. Hopefully, this will also help us understand and explore the role of humans in the AI-Human partnership.
Let’s start with a concrete example: As marketers, we develop our marketing plans with a target market or audience at the centre and make products, services and experiences for them. Then, we let our marketing campaigns run by Meta, Google & Salesforce algorithms to dynamically target audiences for our products/services. We no longer hand-pick our target audiences for the desired products or services. Algorithms have allowed us to scale up, targeting potential customers who are more likely to buy the products or services. As a consequence of algorithms, we may end up with one segment of the audience or market where our products are a success and with another segment where it has failed.
At this exact moment, marketers are usually left with 2 options to take:
- Conduct in-depth research on the 2 segments to understand why there is a difference. Following the research, one can address the challenge with an alternative product offering, personalised communication message, etc.
- Continue investing in what drives the business today.
Over the years, I’ve seen many default to the second option. When asked about it, I usually get a response similar to “if it ain't broke, don't fix it” or “we've always done it this way”.
In addition, there is also an assumption that the first option is a harder route than the second. If you take it at the face value, it may seem so. But, with the advancement of AI & automation, we could actually be doing much more with less.
The very same heavy lifting that algorithms perform for running dynamic marketing campaigns can also be leveraged for research, data analyses and other creative problems.
So, what is stopping someone from going down this road?
- Effort: It takes effort to learn about new technologies, convince key stakeholders, develop a proof-of-concept and scale the program.
- Unlearn & Relearn: During the learning experience, one absorbs information on what works and what doesn’t. Humans are hardwired with historical knowledge and have a tough time unlearning old concepts or ideologies and relearning with newer data/information.
- Short-term vs long-term: In a world of instant gratification, it should come as no surprise that humans prioritise short-term gains over long-term ones due to an uncertain future. A disruptive situation such as COVID-19 or other unforeseen market conditions may have lasting effects on the business sustainability if not ready for the long-term (examples: Nokia in smartphone adoption, Blockbuster vs Netflix, Encyclopedia vs Wiki, etc.).
In many of our corporate organisations, we have finite resources (i.e. time, human and financial capital). Leveraging these resources effectively will be key to success.
But, I believe the “magic sauce” that takes organisations to new levels is the mindset. Using critical thinking, creative problem-solving, perseverance and emotional intelligence not just as a skill, but as a mindset will definitely set us up for a future with AI.
Finally, I leave you with this video from Tom Scott, explaining his AI discovery journey. The unsettling feeling that Tom describes is how we can actually stay on top of it. It’s for this reason, I actively put myself in uncomfortable situations as often as possible.