Over the past three years, activities surrounding AI, particularly generative AI, have been conducted in a wide variety of ways.  In terms of business applications, there are uses ranging from call centers to product development and sales processes.  2025 is being called the first year of AI Agents, and the development of AI that operates autonomously and integrates with existing systems is becoming even more active.  Regarding ways of thinking about that effect, within the perspective of productivity improvement, the reduction of inputs (e.g., the effect of reduced work hours) has been easily understood.
Meanwhile, contributions to growth through the effect of increased output can also certainly occur. A commonly cited direct example of this is 24/7 support provided by AI chatbots. AI can rapidly and continuously handle tasks that humans perform, and so it can dramatically increase the volume of various activities. However, with only activities like these, that same sense of gravity we were made aware of three years ago cannot be felt, and this moment could well be called a period of disillusionment.

Going forward, realizing the major transformation through AI that was initially anticipated will require us to view AI as human capability augmentation in a broader sense. For example, Nomura Research Institute (NRI) views AI not merely as a technical term, but as something that extends human capabilities such as "predictive ability," "discriminative ability," "personalization ability," "conversational ability," "structuring ability," and "creative ability." Rather than simply increasing quantity/volume within existing frameworks, taking risks and challenging ourselves with new things with the power of these forces will create a grand narrative for us as individuals and, by extension, as an organization. In fact, there are research findings showing that utilizing AI can increase a company's risk-taking propensity.
At that time, what will be important is the perspective of how much humans and organizations can entrust to AI. Generative AI is not the only AI. AI encompasses various technologies, including data science techniques such as statistical methods and machine learning, each with its own strengths and weaknesses. The ability to discern these factors will become the foundation of a company's growth potential and competitiveness.

However, we must not forget that new kinds of AI-specific costs and risks will also emerge. It has been pointed out that AI adoption may increase the cost of capital in the short term, as it raises companies' risk appetite while simultaneously increasing their propensity for challenges.
There are also concerns that the black-boxing of AI could create new uncertainties and systemic risks. In AI governance, strict compliance requires significant effort and delays product launches, but on the other hand, being too lenient increases risks. This is a "fundamental question regarding achieving growth" that is unique to the AI era, and whether or not this risk can be effectively controlled will greatly influence competitiveness.
And what becomes important when making decisions about such risky challenges is the "narrative." While business investment decisions require multifaceted perspectives, the most important factor is the growth story. Both investors and managers are drawn to this "story." In the future, AI will also expand the creation of such stories. 

DX has now thoroughly permeated as well. While transformation is certainly necessary, if transformation alone is the goal, it will only lead to exhaustion (DX fatigue). Since labor shortages are an immediate social issue, there is a tendency to become preoccupied with running things efficiently, but as society shifts from deflation to inflation, social consciousness is gradually beginning to turn its attention from cost performance and time performance, which have been important until now, to growth. What kind of growth story lies beyond the transformation? This may well hinge on how much we can utilize AI there.