Personal AI could change who controls the Customer Relationship

The UAE has become the first country in the world where more than seven in ten working-age adults actively use AI, according to the Microsoft AI Economy Institute's first-quarter 2026 report. At 70.1%, that level of AI adoption matters beyond productivity. It offers an early indication of how artificial intelligence could change the way consumers research, compare and make decisions. 

For investors and business leaders, that shift raises a broader question about where customer influence and ultimately commercial value may sit as AI becomes more deeply embedded in the decision-making process. 

As more of that process moves into AI platforms and virtual assistants, a company’s website, app or marketplace page may no longer be the first place a customer encounters it. Personal AI could increasingly sit between customer intent and the businesses competing to satisfy it. 

That creates a new question around the AI customer relationship: if an assistant influences what enters the consideration set before a customer reaches a brand, where does control of that relationship begin? 

Distribution used to belong to the platform 

For most of the digital era, businesses treated direct access to the customer as an asset. Someone who repeatedly returned to the same website, app or loyalty programme was easier to understand, engage and retain. The resulting customer data could help companies build a deeper understanding of customer needs, customer behaviour and purchase decisions over time. 

Platforms had a different advantage: they controlled discovery. Search rankings, marketplaces and social feeds determined which brands captured consumer attention in the first place. 

Brands tried to reduce the distance between themselves and the customer. Platforms monetised the distance that remained. 

Personal AI introduces another layer. 

Instead of sending a user through searches, tabs and comparison pages, generative AI can increasingly absorb a brief, evaluate different data sources, narrow the options and explain the trade-offs before the customer reaches a merchant at all. AI tools can make that process more contextually relevant by incorporating preferences, constraints and previous customer interactions. 

This changes where influence sits across the customer journey. 

Customer data could become more valuable than reach 

Companies already use CRM data, customer interactions, machine learning, predictive analytics and natural language processing to identify patterns, generate actionable insights and improve customer engagement. AI-powered CRM systems can help businesses understand customer behavior, automate workflows and create more responsive customer experiences. 

Personal AI could take this further by connecting context across different parts of the customer journey. While individual companies may only see one part of a customer’s behaviour, an AI system with persistent context could develop a deeper understanding of their needs, preferences and future intent. 

That creates a broader shift: AI-powered CRM helps companies understand customers, while personal AI could help customers understand the market. For investors, this could increase the value of proprietary customer data, trusted transaction infrastructure and businesses positioned close to customer intent. 

Personal AI is becoming the first touchpoint 

McKinsey’s 2026 research across France, Germany and the UK found that consumers are already using AI most heavily before the transaction: 63% for comparing brands, models, prices and reviews, 55% for learning about a category or product, and 46% for discovering new products and finding inspiration. 

In other words, more than half of the consumers surveyed are already using AI during parts of the research and evaluation process. McKinsey’s broader research estimates that agentic commerce could orchestrate between $3 trillion and $5 trillion in global consumer goods commerce by 2030. 

What is more revealing is the point at which AI starts to shape the process. 

Someone looking for a home, an investment product or a new service may increasingly describe the outcome they want to an assistant before visiting a provider. AI systems can conduct an in-depth analysis of available options, interpret unstructured data, compare product information and narrow the field around specific customer needs. 

The same technology already used for product recommendations, AI chatbots and intelligent customer support could therefore become far more influential upstream, where preferences are still being formed. 

That does not mean the merchant disappears. OpenAI’s commerce strategy illustrates the distinction. ChatGPT is placing greater emphasis on product discovery while allowing merchants to retain their own checkout experiences. 

The emerging relationship is therefore distributed across different parts of the journey. The agent may influence what gets considered. The merchant may still control the transaction, fulfilment and service experience. The strategic advantage could sit with whichever participant develops the clearest understanding of what the customer is likely to want next. 

Trust matters more when machines narrow the field 

Digital businesses have spent years competing for consumer attention. An AI-mediated journey changes part of that equation because AI systems need information they can retrieve, interpret and compare. 

As AI plays a greater role in discovery, consistent product information, structured data and evidence-backed claims become more valuable to companies competing for visibility. 

This does not make branding irrelevant. Emotional relevance, service quality and the overall customer experience still influence consumer confidence and customer satisfaction. Human intervention will also remain important in many high-consideration or high-risk decisions. 

But accuracy, clarity and verifiability become increasingly important when an AI system is deciding which options a person sees. 

Data privacy could become equally important. The more personal AI understands customer needs and behaviour, the more valuable that context becomes and the more carefully consumers, companies and AI platforms will need to think about how that data is used, shared and protected. 

Dubai’s real estate tokenization initiative offers a useful example of the type of digitally structured infrastructure that could become increasingly relevant. The Dubai Land Department launched the MENA region’s first tokenised real estate investment project through PRYPCO Mint, a platform connected to PRYPCO, which sits within the AlphaHAS portfolio. 

The initiative was implemented in partnership with PRYPCO and in collaboration with the Virtual Assets Regulatory Authority, the Central Bank of the UAE and Dubai Future Foundation. DLD later introduced a Property Token Ownership Certificate for investors participating through the platform. 

This infrastructure was not built specifically for AI agents. What makes it relevant is the broader shift towards markets where ownership, transaction data and investment processes are increasingly transparent, verifiable and digitally structured. 

If AI platforms increasingly conduct consumer research, compare opportunities and influence purchase decisions, those qualities could become increasingly valuable. 

Consumer context could become the real asset 

The next competitive advantage may come less from reach and more from understanding context. 

Traditional consumer research looks for patterns across groups. AI systems can increasingly identify hidden patterns at the individual level as well, combining customer behavior, previous interactions and preferences to create a more personalized experience. 

For businesses, this opens opportunities to tailor content, improve customer engagement and make interactions more relevant. For consumers, virtual assistants could use similar capabilities to compare the businesses themselves. 

That creates an unusual dynamic. Brands are integrating AI to understand customers more effectively at the same time that consumers are adopting AI tools to understand brands, products and markets more effectively. The resulting AI customer relationship may therefore be less one-sided than previous generations of digital marketing. 

For investors, the relevant question becomes: which companies still have leverage when consumers interact with markets through intelligent intermediaries? 

Businesses with proprietary first-party data, trusted transaction infrastructure, differentiated products or a privileged position close to customer intent could become more valuable. AI may make information easier to process, but genuinely differentiated data, trust and infrastructure remain harder to replicate. 

The competitive edge could increasingly belong to whoever understands the customer before the wider market sees the demand. 

So who owns the customer relationship? 

Customer ownership may become increasingly fragmented. 

AI platforms could influence discovery. Brands may continue to own product and customer experience. Merchants can retain transactions and fulfilment. CRM systems can capture customer interactions after they occur. Personal AI could accumulate context across several of those stages. 

No single participant necessarily controls the entire relationship. 

That is what makes personal AI more significant than another marketing or distribution channel. It has the potential to redraw where information, influence and value sit across the customer journey and, in turn, which businesses are positioned to capture them. 

For investors, the opportunity therefore extends beyond companies building artificial intelligence itself. The more interesting question is which businesses gain leverage as AI becomes a layer between intent and action. 

That is also central to Amira Sajwani’s investment perspective at AlphaHAS: looking beyond the technology itself to where behaviour, infrastructure and ownership are beginning to shift. 

The UAE provides an especially relevant market from which to watch that development. Its high level of AI adoption means the underlying consumer behavior is already evolving at scale.The next winners may be the companies that understand the customer before the customer ever reaches them.