For many of us, it feels like we blinked and suddenly the future was here. Welcome to the world of AI. Because it is not a question of if or when. AI is happening now.
In my industry (marketing insights), AI systems are already poised to take over much of the research process – writing and programming questionnaires, sampling and interviewing respondents, tabulating and modelling results, charting and writing headlines. Even some of the thinking that we believe is uniquely human will soon be done by AI, such as recommendations for the next iteration of ad copy based on test results. Similar transformations are happening across all facets of business.
In response to this, functions across all business units and industries will need to evolve as well. So, what are some of the ways that we can begin to think differently? What are the skills that will be at a premium in the medium term? How do we prepare for this future?
Here are six areas to keep your eyes on (with acknowledgments to the expertise and insights of my global Kantar colleagues J. Walker Smith and Mark Visser):
- Imagination and creativity: While GenAI is being trained to sift through the internet and generate new ideas, AI homogenisation is a real challenge. And while new generations of AI may get better at this, there is the further risk that the training pool has become polluted with AI-generated content that will only make the problem harder to overcome. Therefore, in the near-term, an ability to come up with new ideas and approaches will remain a valuable skill within your business. In fact, the emerging application will be learning how to best take advantage of what AI can do to drive and support human creativity.
- Business acumen: While AI is already better at a single-minded focus of working towards a goal, the setting of those goals – particularly in the face of complex (and sometimes contradictory) KPIs – and adapting them to rapidly changing economic contexts is outside their capabilities for the near term. Having business leaders throughout your structure who understand the business goals and objectives, who can translate into actionable strategies, and adapt these strategies in the face of the changing business context will provide a unique human advantage.
- Critical thinking and problem-solving: As AI focus is on automating routine tasks and streamlining more mundane day-to-day activities, there will be a lag until the next generation of AI can tackle more complex decision-making. So, an ability to analyse complex situations, identify root causes, and develop effective solutions in response will put a premium on human analysts who can apply critical thinking and problem solving. This is not dissimilar to the shift in skills for business leaders when computers were first introduced – they accessed more information more quickly than ever before, putting a premium on their time to consider the data and its context. This shift to needing deeper thinking from leadership is afforded by the time saved through AI in aggregating and summarising information and even the generation of options. The value of the human is in understanding how and why the machines arrive at conclusions, and from there making decisions. Winners will be those who can use their AI powered inputs to chart a course that’s meaningfully different from what the AI has learned from.
- Communication and storytelling: Many of us have had fun getting AI to re-write a document in the style of another author or use AI to summarise a long read or series of documents into something more quickly digestible. The validation of AI output and the ability to generate communication that is clear and persuasive are abilities that remain, for now, uniquely human. And while the former is important, the latter is critical because it impacts the entire organisation’s activation against insights and recommendations. This is, for now, most effectively achieved from the voice of a person with lived experienced rather than computer generated mimicry, and who has used this experience to evaluate and validate the AI summary.
- Empathy and user understanding: Forays into synthetic data have shown that while AI can generate reasonable facsimiles of human behaviours, the interconnectedness of the current deep networks cannot replicate the nuances of human emotion (this limitation exists beyond the scope of the training data, meaning there are already valid applications for synthetic data). Whilst this highlights the importance of ‘real human’ data as the foundation to synthetic data, this limitation also reinforces that a key human skill for the near-term will be interpreting and understanding your customers’ needs and motivations. Not only will this bring to life their humanity, but it will also empower us to create human-centred solutions and activations to business and marketing opportunities.
- Data literacy and ethics: It seems obvious to say that working with AI will require a higher level of data literacy. And fortunately, the business world has been moving in this direction since desktop computers started becoming the norm 30+ years ago. However, the next horizon for data literacy goes beyond mere understanding of data concepts and methodologies behind AI. From the top down, it will be crucial for organisations to have in place both the people and policies that understand the limitations of AI, the risks around what they produce, and who will critically examine to ensure responsible application of their outputs. For day-to-day AI users, data literacy will come to include AI literacy, or specifically “query literacy”: the skill to prompt AIs efficiently and effectively in terms of objectives.
In essence, AI is not replacing business professionals but empowering them to become more strategic, creative and impactful partners in driving growth. To take advantage of this future, we should begin to encourage, train and hire with a premium on Imagination, Business Acumen, Critical-Thinking, Storytelling, Empathy and Data Literacy.
John Cucka – Head of Analytics, Kantar Australia