Business leaders have long been tasked with maximising the potential of human intelligence. But in 2025, they’re not just managing the hearts and minds of people. Leaders must exploit the competitive advantages of AI and empower their human employees to use the technology effectively to steal a march on their rivals.
The majority of businesses are using AI in some capacity. A survey by McKinsey & Company found that 78% of organisations are using the technology in at least one business function. But early experimentation has led to fragmented, disconnected tools in isolation across different areas of the business. And while this might have been a necessary entry point into enterprise AI, companies must evolve their approach as the market and technology mature.
Isolated tools, such as AI-powered customer-service chatbots, are designed to solve specific, niche problems, rather than drive enterprise-wide transformation. This means they have little or no reuse potential in different organisational contexts, limiting their ROI. They also create complexity in the form of siloed data, technical debt caused by using multiple tools and models, and potential security risks in the absence of transparency and controls.
AI tools v an AI-native approach
Simply using AI tools won’t be enough to maintain a competitive edge in the long term. After all, most businesses now have access to all the same technology. Instead, the competitive advantage will be seized by businesses that become AI native. This means moving away from treating AI as just another product or a bolt-on tool for isolated problems. Instead, businesses should embed it at the core of their operations, decision-making and processes for building new products and services.
John Clarke is helping enterprises navigate this change. He’s a senior technology consultant at Telana, a leading provider of AI, data and cloud-technology solutions. The company is helping businesses harness the full potential of AI technology to solve business challenges. Clarke says leaders must begin by adopting an AI-native mindset. This involves a whole organisational view, including building platforms, not just products, using data effectively, upskilling the workforce and adopting a continuous learning approach.
“Leaders are enthusiastic about using AI, but a technology-led approach has resulted in a lot of failed uses,” says Clarke. “If you’re designing a new product, service or process, leaders must understand whether there is actually a business case to solve,” says Clarke. “Is AI the right solution? Will it increase revenue? Will it drive business-wide change? How are you going to measure that? What are the metrics? My job is to get into that detail with leaders and measure the potential impact of an AI solution on operational efficiency, risk and revenue.”
Building an AI operating system
Once those questions have been answered, the next step is to create the necessary infrastructure to facilitate an AI-native transformation. This involves building an AI operating system (OS) that serves as a central hub and nervous system for a business. The aim of an AI OS is to ingest, unify and extract insights from data across a company by considering workflows that connect all departments and integrating key platforms, including for customer relationship management and enterprise resource planning.
The richer the data sources from across the organisation, the more insights and different questions you can ask of it
This enables businesses to weave AI into the fabric of the entire business: the products and services delivered to customers, the internal processes that drive day-to-day efficiency, the skills and mindsets of the people who use it, and the culture that prioritises data-driven, AI-informed decisions. In short, the OS would create an intelligent engine for running a business where AI is the default way an organisation develops.
Clarke says a central OS would generate intelligent and profitable insights that disconnected, siloed systems simply can’t provide. “The ultimate aim is to build platforms, agents and a repository of data built through the AI models,” he says. “It can start to answer multiple types of questions that you might want to ask about that data. The richer the data sources from across the organisation, the more insights and different questions you can ask of it. As a business acquires more data, it will continue to learn, adapt and evolve.”
AI-native businesses in action
Telana is helping traditional businesses such as Channel 4 operate like AI natives. Partnering with the broadcaster, Telana is supporting Channel 4’s ambition to help smaller brands create TV ads using generative AI. This initiative helps address a key market challenge: the high cost and complexity of producing ads that have historically been major barriers for smaller brands.
According to Telana, this AI-native approach enables these firms to punch above their weight. By using AI models to generate broadcast-quality ads, they are making TV advertising more accessible. The next step is to integrate AI into every stage of the creative process, from ideation and storyboarding to compliance checking and publication.
For AI-native startups, this is already their reality. This new generation of companies has been born with AI at its core. AI is the product, the primary workforce and often the key decision-maker. Algorithms are the brains that find market gaps and generate product ideas. They’re also capable of writing and deploying code. Customer support and acquisition are also handled by AI, while financial decisions and transactions are carried out by AI agents. In these businesses, humans oversee tasks but don’t perform them.
These startups provide a competitive warning to legacy organisations. Such companies learn at a much faster rate, with every transaction or click serving as a data point for continuous improvement. They’re capable of making faster and more accurate decisions across key functions such as finance, operations and marketing. Predictive models also minimise risk by spotting forecasting errors and potential customer churn ahead of time.
Businesses that can adapt rapidly to this intelligent new reality will thrive in an AI-native future. Those that don’t will be left behind by competitors who learn, adapt and grow at machine speed.
For more information please visit telana.com
Business leaders have long been tasked with maximising the potential of human intelligence. But in 2025, they’re not just managing the hearts and minds of people. Leaders must exploit the competitive advantages of AI and empower their human employees to use the technology effectively to steal a march on their rivals.
The majority of businesses are using AI in some capacity. A survey by McKinsey & Company found that 78% of organisations are using the technology in at least one business function. But early experimentation has led to fragmented, disconnected tools in isolation across different areas of the business. And while this might have been a necessary entry point into enterprise AI, companies must evolve their approach as the market and technology mature.
Isolated tools, such as AI-powered customer-service chatbots, are designed to solve specific, niche problems, rather than drive enterprise-wide transformation. This means they have little or no reuse potential in different organisational contexts, limiting their ROI. They also create complexity in the form of siloed data, technical debt caused by using multiple tools and models, and potential security risks in the absence of transparency and controls.
