Title: Maximizing Profitability in the AI Era: Tips for Agencies
In the era where AI is set to take over mundane, repetitive tasks, concerns about the financial viability of advertising agencies are valid. Abigail Stuart, the founding partner of Day One Strategy with over 20 years of experience in brand and market research, highlights this concern. As technology automates routine processes, the traditional ways of working and charging clients are becoming obsolete. Forrester predicts that by 2030, U.S. advertising agencies will lose 32,000 jobs to automation, which equates to 7.5% of the total agency workforce (Source: Forrester).
To avoid a price war, agencies must reinvent their business models. For decades, agencies have primarily relied on outputs, not outcomes, to generate revenue. As AI begins to automate previously billed tasks, the billable hour model, which ties income to the effort involved in strategy and creativity, will become less relevant. Agencies must now invest their time predominantly in high-value thinking, rather than process work, and excel in delivering results that clients are willing to pay for.
So, how can agencies add value in this new landscape?
Complementing AI with Human Skills
While AI excels in data analysis, pattern recognition, and instant summaries, it falls short in areas where human expertise is crucial. Agencies can leverage these distinctions to their advantage by capitalizing on the following human strengths:
Asking the Right Questions
AI may be great at answering questions, but it struggles to ask the right ones. Human experience and intuition are invaluable in challenging assumptions, thinking laterally, and posing bold, thought-provoking questions to uncover new opportunities.
Challenging and Provoking
Safety is a thing of the past. Agencies must continue to challenge assumptions and push clients to innovate, focusing on creating value rather than complicating matters. By uncovering hidden opportunities, agencies can help clients stay ahead of the curve.
Bringing Human Empathy
Empathy is a unique human trait. Agencies can leverage this ability to understand diverse audiences, create emotionally resonant campaigns, and navigate sensitive client relationships.
Interpreting Complexity
AI can analyze data but lacks the context and judgment required to translate raw information into meaningful strategies. Human expertise can help identify what matters, simplify complex scenarios, and ensure actions are driven by insight rather than data alone.
Facilitating Strategic Thinking
AI lacks imagination, creativity, and judgment, which are the building blocks of strategic thinking. Agencies can excel in creating environments that foster big ideas, stimulate strategic conversations, and energize groups to bring innovative ideas to life.
Creative Thinking
Machines may generate ideas, but they can't create magic. Human creativity involves leaps of imagination, unexpected connections, and originality, which only humans can bring to the table. Research confirms this, as humans outperform AI in tasks requiring flexible, original ideas (Source: Scientific Reports, 2023).
Instead of viewing AI as a threat, advertising agencies can find opportunities to thrive alongside it by focusing on their core human strengths. By embracing technology, upskilling teams, and shifting their value proposition from outputs to outcomes, agencies can remain relevant and successful in the AI-dominated future.
Abigail Stuart, recognizing this shift, emphasizes the importance of agencies leveraging their human strengths to complement AI. Despite AI's abilities in data analysis and pattern recognition, she emphasizes the role of human expertise in asking the right questions, challenging assumptions, bringing empathy, interpreting complexity, facilitating strategic thinking, and showcasing creative thinking.
Abigail Stuart further emphasizes that, in this new landscape, agencies must upskill their teams to focus primarily on high-value thinking and delivering outcomes that clients are willing to pay for, as the traditional billable hour model becomes less relevant with AI automation.
