In the next five years, businesses will leverage AI to drive transformation or risk being left behind. The accelerating shift toward AI-powered services is happening now. The question for leaders is not whether AI will reshape business but whether they will lead the change or fade into irrelevance.
The Evolution Of Labor: From Historical Systems To AI
Throughout history, evolving labor structures have shaped economic progress. From the labor systems of ancient civilizations and the Roman Empire to medieval serfdom, from the challenging conditions factory workers faced during the Industrial Revolution to the global outsourcing trends of the 20th century, businesses have continually adapted to maximize efficiency and productivity.
Today, AI represents the next major shift in this progression. Companies that adopt AI-driven automation will position themselves for success, while those relying solely on traditional labor-intensive models may struggle to remain competitive.
Evolving From Support To Strategy
The rise of AI is undeniable. A March 2025 McKinsey report found that 71% of surveyed organizations regularly used GenAI in at least one business function. Yet AI adoption remains uneven across industries. A February 2024 MIT Sloan article noted that only 12% of surveyed companies in the manufacturing, information services and healthcare sectors had successfully implemented AI, while sectors like construction and retail lagged at just 4%.
While many organizations still treat AI as a tool to improve operational efficiency, it’s clear that AI is far more than that—it’s a core component of a winning business strategy.
The Pitfall Of Basic AI Adoption: Installing AI Is Not the Same As Transformation
Many companies believe that simply deploying ChatGPT, Microsoft Copilot or another AI tool means they have achieved AI transformation. The initial implementation of basic AI is just the beginning. The value lies in developing custom AI solutions designed specifically for a business’s needs. Companies may face challenges in making full use of the potential of AI if they do not develop a strategy that encompasses more than the use of generic AI tools.
A prime example of an advanced AI-driven system is the enterprise knowledge assistant (EKA) guide, which shows a clear path for organizations to optimize their AI adoption beyond simple integration. However, while this step is the simplest second action after installing AI tools, it is often overlooked.
The Five Levels Of AI Maturity
Imagine you’re walking through the different stages of AI maturity in a business. It all starts with simple automation and moves toward complete autonomy.
• Level 1: AI is reactive—it just follows set rules. Think of things like spam filters or old-school chess-playing programs like Deep Blue. It doesn’t learn or adapt; it’s simply responding to predetermined commands.
• Level 2: AI begins to learn and adapt. It improves over time, like recommendation systems on Netflix or Spotify or even self-driving car algorithms. Here, AI gets smarter and assists with tasks but still requires human oversight and fine-tuning.
• Level 3: AI understands context and can solve problems autonomously. Examples include advanced virtual assistants or AI-powered legal or medical advisors.
• Level 4: AI becomes self-aware, capable of making independent decisions, planning and adapting to new situations without human intervention.
• Level 5: We reach organizational AI, where AI operates entire systems, managing large-scale networks of processes. At this level, AI can run a corporation or even oversee global systems, making high-level decisions with minimal human oversight.
Best Starting Projects With Significant Impact
In my experience, one of the most effective ways to leverage AI is by targeting practical use cases that can make an immediate impact. For example, think about a CNC machine stopping unexpectedly during a shift. It used to be a huge productivity loss, but an AI-powered intelligent troubleshooting assistant can analyze machine data, identify issues and guide technicians to fix the problem within 35 minutes. This drastically reduces downtime.
I’ve seen AI-powered sales assistants analyze customer needs, quickly match them with the right products and provide rapid responses. By using natural language processing, these assistants can understand complex procurement requests and speed up the entire sales cycle. This results in improved conversion rates, better forecasting and more effective upselling and cross-selling.
Another valuable area is EKAs. They centralize institutional knowledge and make it accessible, saving time that would otherwise be spent searching through endless emails and documents.
AI Implementation Best Practices
1. Set clear objectives. Ensure AI aligns with your strategy—improve workflows, quality or client relations.
2. Ensure data quality. Success depends on clean, organized and up-to-date data.
3. Invest in training. Equip your team with the skills to leverage AI effectively.
4. Start small. Test with pilot projects before scaling.
5. Measure and refine. Regularly monitor performance and adjust as needed.
6. Prioritize integration. Choose AI tools that seamlessly integrate with existing systems.
The Verdict: Will You Forge The Future Or Fade Away?
The next five years will define the winners and losers of the AI revolution. Businesses must choose: Will they integrate AI at the core of their operations and become pioneers of the next industrial transformation, or will they remain stagnant, struggling to maintain outdated models until they become irrelevant?
AI-driven business transformation is not a trend—it’s an inevitability. The companies that recognize this and act decisively will not only survive but redefine the future of business itself.
The question remains: Will you fade away, or will you forge the future?
ByBoris Kontsevoi, Forbes Councils Member.
Apr 24, 2025, 07:45am EDT
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