The Future Of AI In Business: Putting The Nail Before The Hammer
Can Generative AI improve your pirouettes? A professional dancer would laugh at this question. Yet in 2023, businesses made similar leaps of faith with GenAI. "Can we use GenAI to fix our analytics? Will GenAI get us better results? Our old methods don't work—GenAI will solve everything!" While GenAI is just the latest phase in AI's evolution, its rapid adoption offers valuable insights about the overall future of AI in business.
In this article, we'll explore how forward-thinking businesses are shaping the future of AI, from strategic implementation to human-centric approaches and emerging technologies that will define the organizations of tomorrow. Specifically, we'll discuss:
- The Promise of Generative AI
- Why Businesses Rushed Generative AI in 2023 & 2024
- Shaping the Future of AI in Business
- Successful Generative AI Implementation With The Estée Lauder Companies
- The Human-Centric Future of AI in Business
- A Better Way Forward: Human^AI for Decision Intelligence
- The Future of AI in Business
- Conclusion
The Promise of Generative AI
Let's talk numbers for a moment. According to McKinsey, Generative AI (GenAI) will automate up to 29.5% of work hours in the U.S. economy by 2030 and boost global GDP by roughly 7%. MIT Sloan's research shows that GenAI can improve highly skilled workers' productivity by up to 40% compared to those who do not use the technology. With projections like these, who wouldn't be excited?
The business world certainly is. In 2023, when executives jumped on investor calls, 'Generative AI' wasn't just a buzzword—it was their golden ticket. Companies that discussed GenAI during these calls saw their stock prices climb 4.6% on average, while those that stayed quiet managed just a 2.4% bump.
Why Businesses Rushed Generative AI in 2023 & 2024
Think back to November 2022, when ChatGPT burst onto the scene. It sparked a gold rush unlike anything we'd seen before. Tech giants like Microsoft weren't just suggesting businesses embrace the technology - they were practically insisting on it. Suddenly, CEOs faced pressure from all sides: boards, internal stakeholders, and competitors. Everyone wanted immediate action plans, strategies, and use cases.
So what happened? Teams jumped in to test and implement GenAI without first figuring out what problems they needed to solve. The excitement of what it could do overshadowed the need to step back and evaluate things carefully.
ECONOMIC IMPACT
Generative AI will automate up to 29.5% of work hours in the U.S. economy by 2030 and boost global GDP by roughly 7%.
We're falling into a classic trap—we’re holding a hammer, so everything’s a nail. We've seen this pattern with every exciting technology that comes along. Teams become mesmerized by its power, viewing it as a miracle solution for everything. When the technology inevitably fails to live up to these inflated expectations, disappointment sets in, and the cycle continues with the next shiny innovation.
Shaping the Future of AI in Business
Successful businesses are figuring out that rushing into AI isn't the answer. Instead of chasing after every new AI tool, they're starting with an important question: "What business challenges are we trying to solve?" “What decisions do we want to make?” Sometimes, AI is the answer, but sometimes, it isn't.
Businesses were trying to use GenAI as a catch-all solution in 2023, yet it turns out GenAI only addresses 10-20% of what organizations need from AI solutions. The other 80% still requires traditional analytics, machine learning, and sophisticated AI strategies. This reality check pushes companies toward a problem-first mindset – a big change from 2023’s tech-driven approach. We must focus on business-driven AI applications that address specific challenges – finding the nails for our hammer – rather than forcing technology into places it doesn't belong.
Another lesson we're learning is that starting small and scaling makes more sense than going all-in. AI technology is evolving so quickly that today's massive implementation might need a complete overhaul next year. While tech giants keep promising seamless platform updates, the reality is that every change disrupts how people work – something that requires careful consideration.
PRODUCTIVITY BOOST
Generative AI can improve the productivity of highly skilled workers by up to 40% compared to those who do not use the technology.
Successful Generative AI Implementation With The Estée Lauder Companies
Want to see this thoughtful approach in action? Look at what ELC is doing.
"We actually don't have a Generative AI strategy. We have a company strategy," as Raheel Khan, SVP of Foresight & Growth Intelligence at The Estée Lauder Companies (ELC), emphasized on an episode of Tech Transformation.
Their focus is clear: create great products and give customers amazing experiences. AI enhances this process through an end-to-end approach. Their Trend Studio platform shows this in action. The platform analyzes millions of daily consumer conversations across social media and review platforms, using AI to surface granular trends for specific consumer segments. Crucially, it then matches these trends to product assets, inventory levels, and execution capabilities.
At the heart of ELC’s success is the "virtuous circle of math and magic." The “math” comes from AI's ability to handle the heavy lifting, while the “magic” stems from human creativity and expertise. Using AI, the company enables its teams to focus their creativity where it matters most – creating products consumers love and developing high-touch experiences that drive repeat purchases.
This exemplifies an effective "nail before hammer" approach. The Estée Lauder Companies identifies its business goals first and then uses AI to help achieve them. Every AI initiative connects end-to-end with its larger strategy, ensuring technology truly serves its business objectives.
The Human-Centric Future of AI in Business
As we look to the future of AI in business, one thing becomes increasingly clear: success depends on human-AI collaboration. While early AI adoption sparked fears of job displacement, forward-thinking organizations are discovering that AI works best when it enhances human capabilities rather than replacing them.
Human experience, context, and judgment will remain irreplaceable. While AI excels at processing vast amounts of data and identifying patterns, humans bring critical thinking, emotional intelligence, personal relationships and years of hands-on experience. The future of business will be built on this powerful combination of human expertise and AI capabilities, creating outcomes neither could achieve alone.
MARKET IMPACT
Companies that mentioned Generative AI during investor calls saw their stock prices rise by an average of 4.6%, while those that didn't only achieved a 2.4% increase.
This human-centric approach to AI is already emerging in technologies like decision intelligence platforms, demonstrating how AI can enhance rather than replace human decision-making. But what exactly is decision intelligence, and why will it be important for tomorrow's businesses?
A Better Way Forward: Human^AI for Decision Intelligence
Let's talk about what really matters in business: making good decisions. Think about it – businesses are basically a collection of decisions, big and small. The typical Fortune 500 company makes around 10 million business decisions every year. And here's the kicker: according to Bain & Company, there's a 95% correlation between how well companies make decisions and how well they perform financially. Make better decisions, get better results. It's that simple (and that complicated).
This is where we need to think differently about AI implementation. Instead of asking, "Where can we use AI?" organizations should ask, "Where do we make decisions?" Because regardless of industry, scale, or type of business, decisions are the foundational building blocks of every organization. They're where data, people, and processes come together to drive action.
That's where decision intelligence platforms (DIPs), like Cloverpop, come in. These platforms provide a unifying framework that helps answer both the "where" and "how" of AI implementation. DIPs blend human expertise with AI capabilities through a structured approach that enhances decision-making at every level – from strategic decisions with long-term implications to tactical decisions impacting day-to-day operations.
Decision intelligence platforms don't just automate decisions. They create a decision-centric environment where AI enhances rather than replaces human judgment. When a company faces a pricing decision, for instance, the platform might analyze market data and make recommendations, but experienced professionals still bring broader context and make the final call. This human-AI collaboration ensures decisions are both data-driven and contextually informed.
Decision intelligence represents the next evolution in how we use AI. Rather than scattered AI implementations, it provides a unified approach that enhances how organizations make choices at every level.
The Future of AI in Business
Experts predict that by 2026, three out of four global companies will use decision intelligence practices. But this is about more than better decision-making—it's part of a bigger change in how businesses operate.
The future of AI in business points toward "intelligent enterprises" where AI technologies work seamlessly across organizations. This integration is poised to reach new levels of sophistication.
IMPLEMENTATION REALITY
Generative AI only addresses 10-20% of organizations' needs for AI solutions, with the remaining 80% requiring traditional analytics, machine learning, and custom solutions.
If we can get to the point where technology and applications are good enough, we'll have AI agents for sales, marketing, HR, and other functions all communicating with each other. These agents will also interact with the marketplace, creating a fascinating world of increased efficiency and effectiveness where companies compete more intelligently.
Conclusion
The future of AI in business isn't about swinging the AI hammer at every problem without first defining and understanding what challenges need solving. Only then can organizations effectively integrate AI to enhance human capabilities. By learning from early adopters, businesses can build smarter organizations that effectively integrate human expertise and AI capabilities. This foundation allows them to embrace approaches like decision intelligence.
Look at Estee Lauder's example – success with AI comes from thoughtful integration that puts people first. The businesses that will thrive are the ones that find the sweet spot between human intelligence and AI capabilities. The result? Organizations that aren't just more efficient but fundamentally smarter in how they operate and compete.
Want to see how Decision Intelligence can help shape your organization's AI future? Schedule a demo today.