The Causality Conundrum: How Ai’s Understanding of ‘Why’ is Reshaping Business Actions

The explosive growth of Ai-based tools in 2023 marked a pivotal shift, not so much in technology itself, but in the way humans behave with each other, their jobs and the psychology of interaction. We’ll look back on this year and view it as the moment in time where we witnessed smarter software and automation becoming more deeply integrated into all of our daily lives, altering how we communicate, learn, and even think about jobs.

At MSQ we saw new ways of working emerging, and these tools, with their advanced capabilities in understanding and generating human-like text and images, started to shape expectations and patience levels. People began to rely on ChatGPT for instant information, creative inspiration, and decision-making support, subtly shifting from traditional, slower methods of problem-solving and creativity.

This reliance on prompt-led workflow for immediate, almost effortless solutions led to a change in how we approach learning, creativity, and even our interactions with each other across the group. The psychological impact was profound – Ai didn’t just offer new tools; it started to redefine the very nature of human curiosity, creativity, and connection.

The integration of tools like Claude for creative ideation and research, MidJourney for rapid visual creations, and GitHub Co-Pilot for programming assistance, has significantly expedited the concept and prototyping process in our work.

They gave us the ability to quickly explore a wide range of possibilities and inspire new directions. However, while they accelerate the initial stages of creativity, what we learned very quickly was that they will never diminish the need for careful craftsmanship and direction in the final execution.

Human learnings

The human touch remains crucial for refining ideas, infusing personal style, and ensuring that the final output resonates with intended audiences. We’re embracing this across all MSQ businesses, using it for ‘Augmented Intuition’ to aid in laying the groundwork, but focusing our human-talents on nuanced artistry, critical thinking, and the emotional intelligence needed to bring creative visions to life and to really deliver on joined-up thinking.

Let’s just go back to my original point, and something we’re exploring across all aspects of the group; Ai brings an interactive paradigm shift, not just a technological one. This is important because while a lot of agency groups and clients have viewed this new Generative-Ai melting pot as a kind of ‘Auto-Magic,’ what we’ve witnessed isn’t magic at all, but a shift to the way we work and behave. We’re witnessing a paradigm shift from traditional, structured interfaces and craft techniques to more intuitive, natural language interactions using chat and prompts.

This evolution is eroding complex menu-driven systems, replacing them with conversational interfaces like chatbots, prompt-boxes and voice assistants. Audiences will also increasingly expect to interact with the world around them in the same way they converse with humans, leading to a significant behavioural shift, and the way we plan and execute our work.

We’ve already seen and felt the need for technical know-how diminishing, making technology more accessible to a broader audience both in-house and with clients. But this also carries its own challenges, because when commands and queries in plain language execute complex tasks in an almost instantaneous way it can be easy to overlook the role that planning and solutionising played in the world without Ai-based tools. It’s now more important than ever to have robust measurements of success and guardrails in place to make sure that quicker output doesn’t equal a damaged NPS.

Safeguarding the next stage

Next year will see the continuation of this evolution with a deeper blend of our digital and physical realities, where seamless, natural interactions with technology become the norm, changing not just how we use software, but fundamentally altering our daily habits and expectations of technological interactions, both inside and outside of the working environment. It’s a culture shift that we’re embracing and training all our staff to be ready for.

In this vast sea of change, turning a large vessel swiftly is not just a matter of steering; every business needs to contemplate and be ready for the ripples that will extend far beyond the bow. We’re under pressure to change and adapt, but such is the course of life and decision-making, that the immediacy of action must be harmonised with the foresight of consequence.

Which is also why in this rapid adoption of innovation, exploration, and behavioural change, it’s never been more important to have robust guardrails, frameworks, governance, and ethics considered and applied, not just nodded too. As the new tools become more integrated into daily life, they present potent opportunities for misuse and the propagation of biases or misinformation, making ethical guidelines vital to ensure responsible use and equitable outcomes.

Moreover, as a data-driven set of businesses, the protection of privacy and data security is critical, so establishing clear ethical standards and governance structures not only fosters trust in these technologies but also ensures that their development and deployment serve the greater good, not just the bottom-line. We’ve implemented Ai guardrail tools that capture what processes and work are being augmented by Ai-based software and scoring those approaches against our own usage policies. It’s given us a very short list of tools and businesses we’ll work with vs. those that look brilliant, and output fun stuff, but don’t hit the same robust standards that we insist on; Never compromise the standard and outcome quality for a quicker output.

More major changes afoot

Finally, that leads us to what’s next in 2024. If we thought this year was disruptive for the marketing, advertising, branding, and digital transformation space, next year will take that to a whole new level. Large Language Models, Neural Networking, Deep-learning, and prompt-based creation have been laying the foundations for the advancement of ‘Causal Ai.’ C-Ai has the potential to flip marketing and CRM industries on their head by finally enabling a deeper understanding of the ‘why’ behind consumer behaviours.

Unlike traditional analytics and machine-learning that identifies patterns and correlations, Causal Ai delves into the root causes of customer actions, offering insights into the intricate dynamics of consumer decision-making. This leap forward allows businesses to tailor more effective, personalised marketing strategies and enhance customer relationship management.

Brands will be able to work with us to fully anticipate needs, predict responses to campaigns, and adapt offerings in real-time, leading to more efficient resource allocation and a significant increase in customer engagement and loyalty. Often before they even know they need it. The shift from correlation to causation in Ai analysis marks a transformative moment, fundamentally altering how businesses interact with and understand their customers. We’re ready for the change both technically, ethically, and culturally, but are you?

Pete Trainor is a Strategy Partner at MMT and the Group Strategy Lead on Ai and Automation at MSQ

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