Long-Term Vision vs. Short-Term Gains - Reimagining Business in the AI Era

In today's rapidly evolving technological landscape, generative AI (GenAI) stands out as a transformative force. Yet, a recent survey by McKinsey found that 75% of companies adopting AI are focused on quick wins and cost reduction. They're deploying chatbots to handle customer service or using AI to automate data entry. While these applications can trim costs and enhance productivity, they miss the bigger picture.

As Satya Nadella, CEO of Microsoft, puts it, "The real power of AI is not in doing things faster, but in reimagining what we can do."

The Pitfalls of Short-Term Thinking

Short-term approaches to GenAI treat it as just another productivity tool. Companies end up with slightly more efficient versions of their current operations, akin to using a sports car to deliver pizza – you might save a few minutes on each delivery, but you're not leveraging the car's full potential.

Consider the case of Walmart, a retail giant that initially implemented AI chatbots to handle customer queries. While this reduced wait times and cut costs, they soon realized they were barely scratching the surface of AI's potential.

As Cheryl Ainoa, Walmart's SVP of New Businesses and Emerging Technology, remarked, "We were so focused on fixing small inefficiencies that we almost missed the opportunity to reinvent our entire customer experience".

Instead of asking, 'How can AI help us do our current tasks faster?' the question should be, 'What entirely new things could we do with AI that were previously impossible?'

Reimagining Business Processes with GenAI

A long-term vision for GenAI revolutionizes how businesses operate across various domains:

Product Development - Short-term thinking might use GenAI to speed up market research or generate product descriptions. However, a long-term perspective reimagines the entire process.

Take the example of Tesla, which has embraced AI throughout its product development cycle. Their AI-driven approach allows for continuous improvement of their vehicles through over-the-air updates, effectively turning cars into learning machines.

As Elon Musk noted, "The car you buy appreciates in value over time rather than depreciates."

This shift moves companies from periodic product launches to a constant stream of innovation, driven by real-time insights.

Strategic Planning - In the realm of strategic planning, the short-term approach uses AI to crunch numbers faster and generate more visually appealing presentations. In contrast, the long-term vision is an always-on strategic advisor, constantly analyzing market conditions, simulating scenarios, and suggesting pivots in real-time.

IBM's Watson for Strategic Planning is a prime example of this approach. It continuously analyzes vast amounts of data from various sources, providing executives with real-time insights and recommendations.

As Laurent Mesnier from L’Oreal put it, "It's like having a team of expert analysts working 24/7, allowing us to make informed decisions at the speed of business"

Transformative Potential Across the Enterprise

The potential of GenAI extends across various business functions, reimagining them in profound ways:

Human Resources - Move beyond AI-driven resume screening to AI-driven talent development. Unilever has implemented an AI-powered platform that creates personalized learning paths for employees, aligning individual growth with organizational needs. The system predicts future skill requirements and suggests relevant training programs, resulting in a 70% increase in internal mobility.

Marketing - Don't just use AI to tweak ad copy. Build systems that dynamically create and evolve entire brand narratives across all channels. Netflix's recommendation system is a prime example, using AI to analyze viewer behavior and preferences to create personalized content recommendations and even influence content creation decisions.

Supply Chain - Instead of merely forecasting demand, create self-adjusting supply networks that autonomously reconfigure based on real-time global conditions. Amazon's anticipatory shipping model uses AI to predict customer orders and move products to local distribution centers before the order is even placed, significantly reducing delivery times.

Customer Service - Rather than automating responses to common questions, build AI systems that proactively anticipate and solve customer needs before they arise. Starbucks' Deep Brew AI platform not only personalizes recommendations but also predicts and resolves potential issues in the ordering process, enhancing customer satisfaction and loyalty.

Shifting the Mindset

Adopting a long-term vision for GenAI requires a fundamental shift in mindset:

1. Focus on Outcomes, Not Activities: As Jeff Bezos famously said, "I very frequently get the question: 'What's going to change in the next 10 years?' And that is a very interesting question; it's a very common one. I almost never get the question: 'What's not going to change in the next 10 years?' And I submit to you that that second question is actually the more important of the two."
2. Embrace Complexity: GenAI excels at handling intricate, multifaceted problems. Google's DeepMind has shown this by solving complex protein folding problems, opening new frontiers in drug discovery and disease treatment.
3. Think Exponentially: Ray Kurzweil, futurist and Google's Director of Engineering, notes, "The future is widely misunderstood. Our forebears expected it to be pretty much like their present, which had been pretty much like their past."
4. Prioritize Adaptability: As Darwin observed, "It is not the strongest of the species that survives, nor the most intelligent that survives. It is the one that is most adaptable to change."
5. Cross Boundaries: Isaac Newton once said, "If I have seen further, it is by standing on the shoulders of giants." This principle is crucial in the realm of AI. The most innovative AI applications often emerge from unexpected combinations of technologies and disciplines. By leveraging advancements in various fields, such as data science, robotics, and natural language processing, companies can develop groundbreaking solutions that transcend traditional boundaries.

Balancing Short-Term Wins with Long-Term Vision

While there is a place for quick wins, they should build momentum and buy-in for bigger changes rather than becoming a crutch. Spotify's journey with AI illustrates this balance. They started with AI-powered music recommendations (a quick win) but have since expanded to using AI in content creation, podcast advertising, and even predicting which songs will become hits.

Navigating Organizational Change

Fully leveraging GenAI will require rethinking roles, skills, and even basic business models.

As Ginni Rometty, former CEO of IBM, puts it, "The only way you survive is you continuously transform into something else. It's this idea of continuous transformation that makes you an innovation company."

Companies like Google and Amazon have created AI-focused roles and departments, invested heavily in employee upskilling, and even restructured their organizations to better leverage AI capabilities.

Forget everything you know about business strategy. In the era of GenAI, incremental thinking is a death sentence. We're not talking about steps forward—we're talking about quantum leaps into uncharted territories of innovation. The companies that will dominate the future aren't improving their processes; they're imagining entirely new paradigms of value creation. GenAI isn't just a new technology—it's a portal to a world of unlimited possibility. But this portal is open for a limited time. Those who hesitate, who cling to the familiar shores of short-term gains, will be left behind as others boldly voyage into new realms of opportunity.

The question isn't whether you'll adopt AI—it's whether you'll have the vision to use it to its full, world-changing potential.