The AI Decade: The New Operating System for Businesses
From using AI to becoming an AI-powered organization
Over the past few years, much of the business conversation around Artificial Intelligence has focused on tools: generative assistants, automation, data analysis, content creation, and, more recently, agents capable of carrying out increasingly complex tasks. But we are now entering a different stage. The question is no longer simply what AI can do, but how it can become an integral part of the way an organization actually operates.
KPMG describes this transformation as one of the defining challenges of today’s “AI decade.” Its analysis shows that many organizations have already invested in pilots, tools, and training, yet far fewer have fundamentally changed how work is structured, how decisions are made, and how value is created.
That distinction matters. Adopting AI does not automatically transform a company. The real shift begins when Artificial Intelligence stops operating as a stand-alone tool and becomes embedded in everyday processes, data, and decision-making.
AI as a new business “operating system”
Describing AI as the new operating system for businesses does not mean literally replacing the technology platforms organizations already use. It is a way of expressing a deeper shift: AI can become a horizontal layer that connects people, information, processes, and technology across the organization.
Until now, a company might have introduced one AI tool for marketing, another for customer service, and a separate automation solution for operations. Each tool addressed a specific need. The next step is to connect those capabilities to the way the business actually runs.
An AI-powered organization can draw on information from multiple systems to spot trends, support decisions, automate selected tasks, and put relevant information in employees’ hands at the right moment. In this model, AI is no longer an add-on; it becomes part of day-to-day operations.
The real transformation happens in the processes
One of the strongest messages in KPMG’s analysis is that adopting technology without redesigning the work around it limits the value that technology can deliver. For example, a tool that can analyze documents in seconds may improve efficiency. But its impact becomes much greater when the company also rethinks what happens next: who uses the information, what decision needs to be made, which system should be updated, and which follow-up tasks can be automated.
The same logic applies across the business. In sales, AI can help assess opportunities and prioritize prospects. In operations, it can identify patterns and support process automation. In customer service, it can help teams respond using information pulled from different systems. And in Business Intelligence, it can help interpret large volumes of data and make insights easier to access.
The value does not come from the AI model alone, but from how its capabilities are embedded in a complete business process.
Data, systems, and people: the foundation of an AI-ready organization
For this transformation to happen, AI needs more than advanced models; it needs reliable data. An organization may have access to powerful Artificial Intelligence tools, but if its information is fragmented across ERP, CRM, ecommerce platforms, spreadsheets, and other applications that do not communicate effectively, consistent results will be much harder to achieve.
That is why becoming an AI-powered organization also requires attention to system integration, data quality, and technology architecture. But there is another dimension that matters just as much: people.
KPMG emphasizes that success in this new stage depends not only on adopting AI, but also on workforce readiness and the transformation of the operating model. Companies need to define where AI can create value, which activities should continue to rely on human judgment, and how people and AI can work together effectively.
From experimentation to business value
Many organizations began their AI journey with pilot projects. That stage has been valuable for learning, experimenting, and understanding what the technology can do. The challenge now is to move toward applications that produce measurable business outcomes.
That means moving beyond the question, “Where can we use AI?” and asking questions that start with the business instead: Which process needs improvement? Where are repetitive tasks consuming too much time? Which decisions would benefit from faster access to information? What data do we already have? And how will we measure whether the implementation is actually creating value?
This shift in perspective helps prevent AI from becoming a collection of disconnected initiatives.
Transformation also requires governance
As AI becomes more deeply embedded in business processes, organizations also need clearer rules for how it is used. The data that models rely on, access permissions, privacy, human oversight, and accountability for certain decisions all become part of the strategy.
This was also a key topic at IA-TEC 2026, where AI governance was discussed alongside business applications, innovation, and customer experience. Becoming an AI-powered organization, therefore, is not about automating everything that can be automated. It is about deciding what should be automated, what should remain under human supervision, and what rules each solution should operate under.
The advantage will come from connecting AI to the business
Over the course of this decade, we are likely to see a widening gap between organizations that simply use AI tools and those that successfully embed AI into the way they operate. The first group may achieve incremental productivity gains. The second will be able to rethink processes, connect information more effectively, accelerate decision-making, and develop new ways of working.
This is one of the central ideas in KPMG’s analysis: the challenge is not simply technology adoption, but what that adoption is ultimately meant to transform inside the organization.
From that perspective, AI can be understood as a new business operating system—not because it replaces existing technology, but because it is beginning to function as an intelligence layer that cuts across processes, data, systems, and decisions.
Sphere and the shift toward AI-powered organizations
At Sphere IT Consulting, we approach this transformation from an end-to-end perspective. Adopting Artificial Intelligence requires a clear strategy aligned with business priorities, leaders committed to driving change, teams prepared to apply it, and a deep understanding of the processes and systems that support daily operations. From there, capabilities such as AI, automation, data platforms, integrations, and software development can be combined to address specific business needs.
Our participation in IA-TEC 2026, the International Congress on Artificial Intelligence and Technology, organized by the Lima Chamber of Commerce on September 1 and 2, gave us an opportunity to deepen our knowledge and exchange ideas on topics including Artificial Intelligence, Data and Analytics, automation, cloud services, and digital transformation.
For Sphere, events like this are an opportunity to broaden our perspective on technological change and continue exploring how companies can put these capabilities to practical use. The goal is not to adopt AI simply because it is a trend, but to identify where it can create value and connect it with the right data, systems, and processes.
The AI decade is already underway. The real challenge for companies will not be simply to use Artificial Intelligence, but to integrate it strategically into the way they operate, make decisions, and evolve.
Reference source:
KPMG — Reorganise or fall behind: The real race in the AI decade