The interest in AI remains substantial due to its anticipated influence on value creation in the coming decade. As per PwC, AI has the potential to contribute significantly to the global economy, with an estimated reach of $15.7 trillion by 2030 and McKinsey estimated the annual global impact of AI at $13 trillion. At an organizational level, AI’s influence is evident in the accomplishments of various AI Achievers who have successfully integrated AI into their operations with up to 30% or more of revenue attributed to AI. Therefore, it’s not surprising that many businesses are eager to draw lessons from these AI Achievers to replicate their successes. However, how do AI Achievers leverage the Power of AI?

Leveraging AI for Business Growth

AI’s potential for creating business opportunities is intricately linked to its specific application areas, namely AI for process optimization, decision augmentation, automation, and the development of AI products and services (Proksch et al. 2024).

Process Optimization: In the realm of process optimization, AI can streamline and enhance existing business processes. Nevertheless, its impact is confined within the boundaries of those processes. While AI excels at cost reduction, its potential for creating substantial growth is limited. This type of AI application often represents low-hanging fruit with a relatively modest business opportunity. However, the feasibility and adoption risks associated with this application are also relatively low.

Example: In the manufacturing industry, AI-powered predictive maintenance systems analyze data from sensors on machinery to predict when a component is likely to fail. This enables timely maintenance, reducing downtime and saving on repair costs.

Decision Optimization: AI’s role in decision augmentation and automation delves deeper into business processes. These applications can indeed foster growth beyond mere cost-cutting by improving operational efficiency. However, their impact is restricted to the specific operations they support. The associated risks, notably the risk of incomplete technology adoption across the entire enterprise, become increasingly significant.

Example: In the healthcare industry, AI diagnostic tools assist radiologists in interpreting medical images like X-rays and MRIs, leading to faster and more accurate diagnoses.

AI Product Creation: Conversely, the creation of products and services with AI’s assistance is perhaps the most promising area of application. It opens up almost limitless growth potential from a business standpoint. However, the challenges of feasibility and customer adoption are formidable. These hurdles explain why over 90% of AI startups do not succeed.

Example: Amazon Echo with Alexa is a prominent example of an AI product that has created business value through innovative AI technology, offering users convenience and enabling Amazon to expand its ecosystem and services.


In summary, while there are many potential applications of AI, the choice of AI application area must align with a company’s strategic objectives and risk tolerance. While process optimization offers relatively low business opportunities and risks, decision augmentation and automation enable more growth but involve increased risks. The creation of AI-based products and services holds the most significant growth potential but comes with substantial feasibility and adoption challenges. Understanding these trade-offs is crucial for making informed decisions regarding AI implementation.