SKYWARE AX INSIGHTVol. 01
How leading global thinkers see change in the AI era, and what it means for enterprise AX transformation
October 13, 2026 | SKYWARE AX INSIGHT
Artificial intelligence (AI) has moved beyond simply assisting with tasks and is now shaping corporate decision-making, organizational management, customer experience and industrial competitiveness as a whole. Many companies agree that AI adoption is necessary, yet questions remain about how to actually use it in their business and what results it should deliver.
EBS’s series “AI Masters Lecture: Next Vision,” airing since September 2026, offers a valuable perspective for understanding the essence of this change. World-renowned thinkers including Yuval Noah Harari, Salman Khan, Ray Kurzweil and Erik Brynjolfsson each examine, from their own fields, the changes AI will bring and the challenges people need to prepare for.
In this insight, we look at the key changes of the AI era and the AX (AI Transformation) strategies companies should prepare, based on the lecture topics released as of October 13, 2026.
01. AI Is Changing the Structure of Decision-Making
Historian Yuval Noah Harari draws attention to the possibility that, as AI goes beyond delivering and selecting information to taking part in decision-making, it could reshape the structures of social power and control. This perspective carries important implications for the business world as well.
Companies already use algorithms in many areas, including customer data analysis, product recommendations, demand forecasting and marketing strategy. As AI participates in more decision-making processes, companies will need to consider not only AI’s performance but also the reliability of its judgments and the structure of accountability.
When introducing AI into core business operations in particular, it is important to have data accuracy, access permissions, result verification and a framework for final human approval in place. Rather than a system that simply executes whatever AI suggests, building a system the organization can trust and control is the starting point for sustainable use of AI.
02. The Core Competitive Edge of the AI Era Is Collaboration Between People and Technology
Khan Academy founder Salman Khan presents the potential to transform education through personalized learning and AI learning assistants. The same approach can be applied to how companies develop talent and how work gets done.
If AI supports information search, document organization and repetitive analysis, employees can spend more time on defining problems, thinking creatively, communicating with customers and making strategic judgments.
What matters is not just how skillfully people operate AI. The ability to clearly define the problem to be solved, design the right questions and judge whether AI’s output is sound is becoming even more important. Corporate AI transformation should therefore go hand in hand with technology adoption and redesign employees’ capabilities, roles and work processes.
03. Companies Need a Structure That Can Keep Pace with AI
Futurist Ray Kurzweil foresees accelerating technological progress and the potential expansion of human capabilities. Although there is uncertainty about when the future he describes will arrive, the lesson for companies is clear: rather than depending on a specific technology or a single solution, they must build a digital foundation that can adapt flexibly to change.
APIs, standardized data structures and a scalable platform architecture that can connect existing business systems with AI form an important foundation for putting new technologies to work. Companies should not stop at one-off AI adoption, but create an environment where AI is connected to existing business systems and continuously improved.
04. The Economic Value of AI Is Proven by Real Productivity
Economist Erik Brynjolfsson has studied the changes AI will bring to industries, labor markets and economic productivity. For companies, the value of AI becomes clearest when it is tied to actual business performance, rather than to the performance of the technology itself.
An e-commerce company adopting AI, for example, can set concrete goals such as reducing the time spent managing product information, handling customer inquiries more efficiently, optimizing campaign operations and improving customer experience. In this process, success should not be judged simply by the number of employees using AI or the number of solutions deployed.
The impact must be verified through tangible metrics such as processing time, error rates, customer response quality, conversion rates and operating costs. The ultimate goal of AI adoption is not automation for its own sake, but greater productivity and business competitiveness.
05. From AI Adoption to AX Transformation
AI adoption and AX transformation should be distinguished. If AI adoption means applying new technology to individual tasks, AX transformation is the process of redesigning a company’s work processes and way of operating around AI. Using AI to write marketing messages sent to customers, for instance, is an individual AI use case.
Going further, organically connecting customer data analysis, target segmentation, message generation, delivery and performance analysis can evolve into an AX transformation that improves the entire marketing operations process.
In e-commerce, too, companies need to go beyond automating individual functions such as product registration, inventory management, customer service and personalization, and review the entire operational flow in an integrated way. The key tasks companies should prepare for AX transformation are as follows.
- AI readiness assessment Objectively assess the current work environment and level of data use
- Core task selection Identify initiatives that improve both operational efficiency and business performance
- Technology and system integration Reliably connect existing business systems with AI technology
- Operations and control framework Establish security, privacy protection, verification and accountability for decisions
- Performance-driven enhancement Continuously measure and improve the impact of adoption
SKYWARE Proposed Model
Enterprise AX Transformation Framework
- 01AssessWork · Data
- 02DesignPriorities
- 03ValidatePoC testing
- 04IntegrateSystem integration
- 05EnhancePerformance · Control
- E-commerce AXPersonalized recommendations using product and customer data, plus automated product information management and operations
- AI MessagingSupport for message content generation, customer segmentation and campaign performance optimization
- Enterprise Work AXInternal document search, handling of repetitive tasks, report writing support and integration with approval processes
- AI GovernancePrivacy protection, AI access permissions, approval and verification, and log management
- AX ConsultingAI readiness assessment, identification of core initiatives, PoC execution and performance measurement
06. Beyond Technology Adoption to Business Transformation
Although the lectures by these world-renowned thinkers cover different fields, from a business perspective they all lead to one important question.
Beyond what AI can do, what will we change about our company through AI?
If a company cannot clearly define the problems it needs to solve, it will struggle to achieve the expected results even with outstanding AI technology. Conversely, if it fully understands its business goals and the nature of its work and applies the right technology, AI can become a genuine driver of innovation.
From the perspective of e-commerce solutions and enterprise system development, SKYWARE continuously explores how AI technology can translate into real business value. Grounded in an understanding of both technology and business, the essence of AX transformation is enabling companies to apply AI to their actual work and services and secure sustainable competitiveness.
Competitiveness in the AI era is not achieved simply by being first to adopt technology. It comes from the execution capability to turn technology into business change.