How AI Is Reshaping Market Dynamics
Why Buying Decisions Are Changing First
In Brief
Artificial intelligence is not only changing how organisations operate — it is changing how markets operate. AI systems increasingly perform the discovery, interpretation and evaluation that buyers once performed themselves. Because markets allocate demand through those mechanisms, buying decisions are the first place the change becomes visible.
- Markets coordinate supply and demand through discovery, trust, interpretability, evaluation, selection, distribution and competition.
- Historically, the cognitive work connecting these mechanisms was overwhelmingly human.
- AI now performs a growing share of that work, before buyers engage suppliers directly.
- Visibility remains necessary but is no longer sufficient.
- Competition shifts upstream: organisations compete to enter the decision process, not only to win it.
1. The Rules of the Market Are Changing
Much of today's discussion surrounding artificial intelligence focuses on organisational capability. Boards debate productivity gains, executives invest in copilots and automation platforms, and management teams seek new ways to improve operational efficiency through generative AI. These developments are significant, but they also risk drawing attention away from a more fundamental transformation already underway.
Artificial intelligence is not simply changing how organisations operate.
It is changing how markets operate.
This distinction matters because markets are not static environments within which organisations compete. Markets are dynamic coordination systems. Their primary function is to connect buyers seeking solutions with organisations capable of providing them. Competition emerges from the mechanisms that enable this coordination to occur efficiently under conditions of uncertainty.
Throughout economic history, enduring shifts in competitive advantage have rarely been driven solely by technological improvements in products or production. Instead, they have followed changes in the mechanisms that connect supply with demand.
The railway expanded the physical reach of markets by reducing the cost and time required to move goods. Telecommunications accelerated the movement of information across distance. Mass media transformed how organisations communicated with large audiences. The internet dramatically reduced the cost of finding and exchanging information, allowing buyers to compare alternatives across global markets with unprecedented ease. Each of these transitions altered market dynamics because they changed how buyers and sellers interacted. (Donaldson and Hornbeck, 2016; Goldfarb and Tucker, 2019)
Yet one characteristic remained remarkably consistent. The cognitive work required to transform information into decisions remained overwhelmingly human. (Simon, 1955; Stigler, 1961)
Regardless of how information reached them, buyers continued to perform the essential activities that underpin every market. They identified potential suppliers, interpreted available information, assessed credibility, compared competing alternatives and ultimately decided which organisation to trust. Technology increasingly improved access to information, but human judgement remained the principal mechanism through which markets allocated demand.
Artificial intelligence represents a different category of technological change. Rather than merely accelerating the movement of information, AI increasingly participates in the cognitive activities that convert information into decisions. (OECD, 2024)
When an executive asks an enterprise assistant to recommend software vendors, when a consumer requests a personalised product recommendation from a conversational AI, or when a procurement team uses generative AI to identify suitable suppliers, the system is doing more than retrieving information. It is beginning to perform elements of discovery, interpretation, comparison and recommendation that have historically been carried out by human decision-makers. (OECD, 2024; Brynjolfsson, Li and Raymond, 2025)
This represents a subtle but profound shift. The internet transformed how information moves through markets. Artificial intelligence is beginning to transform how decisions are made within markets.
Understanding this distinction is essential because information and decisions play fundamentally different roles in economic coordination.
Information expands choice. Decisions allocate demand.
For decades, digital technologies primarily increased the amount of information available to buyers. Search engines, marketplaces and digital platforms dramatically expanded market transparency while preserving the buyer's central role in evaluating that information. AI increasingly changes the location of that evaluation. Instead of simply providing information, intelligent systems are beginning to interpret, synthesise and assess it before buyers engage directly with competing organisations. (Goldfarb and Tucker, 2019)
This does not imply that AI replaces human judgement. Strategic purchasing, investment decisions and complex enterprise procurement continue to depend upon human expertise, organisational priorities and contextual understanding that extend well beyond algorithmic recommendations.
However, it does change where a growing share of cognitive work occurs. Increasingly, buyers begin their decision-making process with information that has already been organised, interpreted and prioritised by AI systems.
The consequence extends beyond individual buying behaviour. As AI assumes a greater share of the cognitive work connecting buyers and sellers, the mechanisms through which markets operate begin to change. Organisations no longer compete solely for human attention. They increasingly compete within decision processes in which AI actively participates. (OECD, 2024)
Buying decisions are therefore not the phenomenon themselves. They are the earliest observable manifestation of a deeper structural transformation.
To understand why buying decisions are changing, it is necessary to examine the mechanisms through which markets allocate demand — and how artificial intelligence is beginning to reshape those mechanisms.
2. How Markets Operate
Markets are frequently described through the language of economics: supply and demand, pricing, market share and competition. These concepts explain important economic outcomes, yet they reveal less about how organisations actually compete for customer choice.
At a practical level, every market performs a coordinating function. It connects buyers seeking solutions with organisations capable of providing them.
That coordination is not achieved through a single event. It emerges through a connected set of cognitive and institutional mechanisms that transform an initial need into a commercial outcome. Buyers rarely possess complete information, and organisations rarely have complete knowledge of buyers' preferences. Search costs, information asymmetries and bounded rationality therefore shape how markets function. (Akerlof, 1970; Stigler, 1961; Simon, 1955)
Seven mechanisms are particularly important to this process: discovery, trust, interpretability, evaluation, selection, distribution and competition. Together, they describe how organisations become visible, understandable, credible, comparable and ultimately chosen.
This article develops the mechanisms most directly affected by AI-mediated cognitive work—Discovery, Interpretability, Evaluation, Selection and Distribution. Trust and Competition remain part of the same seven-mechanism architecture, but function as supporting mechanisms within this article and are developed further in subsequent research.
They should not, however, be understood as independent stages. They form a connected system.
The important point is that buying decisions do not exist independently of these mechanisms; they emerge from them.
For most of modern economic history, buyers performed much of the cognitive work connecting these mechanisms. A procurement manager researching suppliers, an investor assessing companies or a consumer choosing a product would search for information, interpret evidence, judge credibility, compare alternatives and form a decision. (Simon, 1955; Stigler, 1961)
Technology supported these activities without fundamentally relocating them. Search engines accelerated information retrieval. Digital marketplaces expanded access to alternatives. Review platforms aggregated signals of trust. Comparison tools structured information. Yet the essential act of transforming that information into a decision remained predominantly human.
Artificial intelligence begins to alter this allocation of cognitive work.
Rather than merely helping buyers access information, AI increasingly performs a growing proportion of the reasoning that connects information to decisions. This is consistent with the broader economic literature describing AI as a general-purpose technology whose effects can extend beyond individual applications into organisational and economic processes. (Agrawal, Gans and Goldfarb, 2019; OECD, 2024)
The mechanisms themselves remain recognisable. Discovery still precedes understanding. Understanding still precedes evaluation. Evaluation still precedes selection. What changes is who performs more of the cognitive work within those mechanisms.
This distinction provides the central explanatory mechanism for the remainder of this article.
The growing use of AI assistants, generative search, enterprise copilots and agentic systems can appear to represent separate technological developments. Yet viewed through the mechanisms of the market, they reveal a common pattern: AI is increasingly performing activities that buyers historically performed themselves. (OECD, 2024)
This shift exists on a continuum. In some settings, AI supports the buyer by identifying and evaluating alternatives before a human makes the final decision. In others, increasingly through agentic systems, the buyer can delegate the selection itself and allow the system to act within defined parameters. The significance is the same: cognitive work that historically connected buyers with sellers is increasingly performed by machines, with the boundary between recommendation, decision and execution becoming progressively less distinct.
Discovery changes because AI increasingly identifies potentially relevant organisations. Interpretability changes because AI must construct an understanding of an organisation before it can reason about its suitability. Evaluation changes because AI increasingly compares alternatives against a stated objective. Selection changes because recommendations increasingly emerge from those preceding processes. Distribution changes because these activities increasingly occur inside AI-mediated environments rather than conventional information channels.
The mechanisms remain connected. The cognitive work is increasingly shared. That is why buying decisions change. More importantly, it is why market dynamics change.
Markets have historically relied heavily on human cognitive work to transform information into commercial decisions. Artificial intelligence increasingly performs part of that work. (OECD, 2024; Brynjolfsson, Li and Raymond, 2025)
3. Discovery Becomes AI-Mediated
Discovery has always been the entry point into market competition. Before any organisation can be evaluated or selected, it must first become discoverable.
Throughout history, this has been achieved through successive waves of distribution technology. High streets, catalogues, television advertising, search engines and social media all changed how buyers encountered products and services, but they shared a common characteristic: they primarily helped people navigate information themselves. (Goldfarb and Tucker, 2019)
Artificial intelligence changes this relationship.
This shift is not entirely new. Search engines, recommendation systems and ranking algorithms have already performed forms of machine-assisted discovery, comparison and prioritisation for decades. The difference is not that machines have suddenly begun influencing evaluation. It is that generative AI increasingly integrates discovery, interpretation, evaluation and recommendation within a single decision process, allowing buyers to express an objective in natural language and receive a synthesised set of options rather than navigating separate information sources themselves.
Increasingly, buyers no longer begin with lists of options. They begin with questions.
Rather than searching for dozens of potential suppliers, they ask conversational systems to recommend the most appropriate software platform, identify a suitable legal adviser, compare investment products or suggest the best destination for a particular type of holiday. Enterprise procurement teams are experimenting with AI-assisted vendor research, employees use enterprise copilots to locate internal expertise, while consumers increasingly rely on generative AI assistants to synthesise information gathered from multiple sources. (Stanford HAI, 2026; BCG, 2026a)
The interface remains conversational, but the structural implication is much deeper.
Discovery is becoming mediated rather than navigated.
Instead of presenting a broad collection of links for users to explore, AI systems increasingly perform part of the discovery process themselves. They gather information from multiple sources, synthesise competing claims and present a significantly narrower set of options aligned with the user's stated objective. (BCG, 2026a)
Traditional digital discovery largely rewarded visibility. Appearing in search results increased the probability of consideration because human users still performed much of the interpretation and evaluation themselves. (Goldfarb and Tucker, 2019)
AI-mediated discovery shifts more of that cognitive work upstream. The system itself participates in determining which organisations deserve further consideration. (Bak, Kalthof and Schwartz, 2025; BCG, 2026a)
Attention expands possibilities. AI-mediated discovery narrows them. This narrowing does not necessarily reduce competition. In many cases, it may intensify competition because fewer organisations progress into the stages of the buying process where human judgement, commercial negotiation and product differentiation can exert meaningful influence.
This does not imply that human judgement disappears. Complex purchasing decisions continue to involve multiple stakeholders, organisational politics and contextual considerations. However, AI increasingly shapes the initial decision environment within which those human judgements occur.
In effect, discovery begins moving away from being an open exploration of available information towards a structured process of identifying plausible candidates.
The consequence is that market participation increasingly depends not only on whether an organisation exists within the available information landscape, but whether AI systems recognise it as relevant to the specific context in which a decision is being made.
This naturally leads to a deeper question. Before AI can evaluate an organisation, it must first understand it.
4. Interpretability Becomes a Competitive Requirement
Interpretability is likely to become one of the least discussed yet most important competitive capabilities emerging in AI-mediated markets. This sense of interpretability is distinct from interpretability in machine learning, which refers to explaining a model’s internal behaviour.
Human buyers possess remarkable contextual intelligence. They infer meaning from incomplete information, reconcile inconsistencies, interpret nuance and fill gaps using experience and judgement. Organisations have long relied on these capabilities. (Simon, 1955)
Artificial intelligence operates differently.
Before an AI system can recommend an organisation, it must first construct an internal representation of what that organisation is, what it offers, which problems it solves and under what circumstances it is relevant. (Agrawal, Gans and Goldfarb, 2019; OECD, 2024)
Interpretability therefore precedes evaluation.
Discovery asks whether an organisation is potentially relevant. Interpretability asks what that organisation is, what capabilities it possesses and when those capabilities should matter. An organisation that cannot be interpreted consistently cannot be evaluated consistently.
Interpretability enables evaluation. Evaluation enables selection.
If the system cannot accurately determine what an organisation does, who it serves or how it differs from alternatives, meaningful evaluation becomes impossible. The organisation risks exclusion because it cannot be interpreted with sufficient confidence. (OECD, 2024)
Interpretability therefore becomes more than an information challenge. It becomes a competitive requirement.
In the next section, we examine what happens once AI has formed that understanding — and why evaluation itself is beginning to change.
5. Evaluation Becomes Machine-Assisted
Interpretability alone does not determine competitive outcomes.
Once an AI system has formed a coherent understanding of an organisation, it must determine whether that organisation represents an appropriate response to the buyer's objective. This transition — from understanding to judgement — is the function of evaluation.
Evaluation has always occupied a central position within market coordination because buyers rarely possess complete information and rarely face objectively correct choices. They compare alternatives under uncertainty, balancing competing objectives and estimating which organisation is most likely to satisfy a particular need.
Historically, this cognitive work was overwhelmingly human. Digital technologies improved its efficiency. Search engines reduced the cost of finding information. Analyst reports synthesised expertise. Reviews aggregated customer experiences. Comparison tools structured product information. Yet these technologies largely supported human reasoning.
Artificial intelligence increasingly performs an initial layer of comparative reasoning before information reaches the decision-maker.
Research already provides evidence that generative AI can perform parts of knowledge work previously requiring substantial human analysis. Brynjolfsson, Li and Raymond's field study of 5,172 customer-support agents found that access to a generative AI assistant increased productivity by approximately 15% on average, with particularly strong effects among less experienced workers. The study is about work rather than market selection, but it provides relevant evidence for the broader proposition that AI can transfer elements of previously human cognitive work into machine-assisted workflows (Brynjolfsson, Li and Raymond, 2025).
In market contexts, the same structural shift is beginning to appear through recommendation and comparison systems. AI can synthesise multiple sources, identify patterns, compare alternatives and generate recommendations aligned with an interpretation of the buyer's objective. BCG's recent research on AI-mediated consumer journeys similarly describes AI systems as moving beyond browsing towards recommendation and purchasing assistance. (BCG, 2026b)
The significance is not simply that evaluation becomes faster. It changes who performs the initial evaluation.
Historically, buyers constructed a broad consideration set and then evaluated the alternatives. AI increasingly reverses this process. The buyer may begin with a smaller set of organisations that has already undergone an initial layer of machine-assisted assessment. Human evaluation therefore shifts from constructing the decision environment to validating or interrogating a recommendation.
This does not imply that AI possesses objective judgement. Its assessments remain contingent on the information available to it, the task it has been given and the reliability of its reasoning.
The strategic point is narrower. If AI performs an initial evaluation, organisations increasingly compete within that evaluation before they engage the buyer directly.
The criteria are familiar:
- relevance
- authority
- credibility
- fit for purpose
What changes is where and by whom these criteria are initially assessed. Evaluation therefore becomes an increasingly important mechanism through which AI participates in allocating attention and opportunity.
Once evaluation narrows the field, the market moves to selection.
6. Selection Becomes Compressed
Every commercial interaction ultimately converges on a single outcome.
One organisation is selected.
Historically, selection followed an extended sequence. Buyers discovered potential suppliers, gathered information, interpreted competing claims, evaluated alternatives, consulted colleagues and progressively narrowed the field before committing to a decision.
Artificial intelligence increasingly integrates these activities.
When AI participates in discovery, interpretability and evaluation, it also influences selection. Rather than presenting buyers with a broad universe of alternatives requiring extensive independent comparison, AI systems increasingly return a limited set of recommendations that reflect an integrated assessment of the user's objective.
Selection therefore begins earlier than many organisations assume. It no longer exists solely as the final stage of the buying journey. It increasingly emerges throughout the interaction as AI systems interpret intent, compare organisations and refine recommendations.
This explains why AI-mediated buyer journeys can become compressed.
The compression does not mean that every decision becomes instantaneous. Enterprise procurement, strategic investments and complex purchases will continue to involve governance, negotiation and human judgement.
Instead, compression reflects the integration of previously separate cognitive activities. Discovery, interpretation, evaluation and recommendation increasingly occur within a single interaction before buyers undertake detailed independent analysis. The buyer therefore encounters a market that has already undergone substantial cognitive processing.
This changes competition. Historically, organisations competed within the buyer's evaluation process. Increasingly, they compete to enter that process.
An organisation excluded during AI-mediated evaluation may never reach the stage at which traditional competitive advantages — brand reputation, sales capability, product differentiation or relationships — can influence the outcome.
Competition therefore shifts upstream. Organisations increasingly compete not only to persuade buyers but to become candidates for persuasion.
This is a cumulative consequence of the preceding mechanisms. Discovery determines whether an organisation is encountered. Interpretability determines whether it can be understood. Evaluation determines whether it appears appropriate. Selection determines whether it proceeds into meaningful commercial engagement.
The sequence remains intact. Its execution becomes increasingly integrated.
7. Distribution Is Becoming AI-Mediated
Distribution has always determined the practical boundaries of competition. Railways expanded physical distribution. Retail networks expanded consumer access. Broadcast media expanded communication. Search engines and digital platforms transformed the connection between buyers and information. Each transition reshaped markets because it altered where commercial interactions occurred.
Artificial intelligence introduces another transition, but with an important difference.
AI increasingly participates within the decision process itself. Search engines primarily enabled navigation. AI increasingly enables recommendation. That distinction changes the role of distribution.
Rather than simply directing buyers towards available information, AI increasingly organises, interprets and prioritises that information before presenting a structured representation of the market.
Distribution therefore becomes progressively intertwined with reasoning. The environments through which buyers encounter organisations increasingly become environments within which decisions themselves are partially constructed.
This development is already visible in the consumer market. BCG's research (BCG, 2026b) indicates that shoppers increasingly use generative AI to guide brand and product choices, while its work on AI-first retail argues that AI systems are beginning to recommend products rather than merely direct consumers to destinations. (Bak, Kalthof and Schwartz, 2025)
The implication extends beyond consumer behaviour. Market access itself begins to change.
During the internet era, organisations competed for visibility across search engines, marketplaces, media channels and social platforms.
In AI-mediated markets, organisations increasingly compete for participation within recommendation environments where discovery, interpretation, evaluation and selection occur together.
Distribution therefore becomes less concerned with directing traffic and more concerned with participating within AI-mediated decision pathways.
This is not simply another digital channel. It is a structural evolution in market coordination.
The internet changed where buyers found information.
Artificial intelligence increasingly changes how information becomes decisions.
8. Strategic Implications
The implications of this transition extend beyond technology strategy. They challenge assumptions that have shaped competition throughout much of the digital era.
For decades, organisations sought competitive advantage by increasing visibility. The underlying logic was straightforward: greater exposure created greater opportunity because buyers remained responsible for interpreting information, comparing alternatives and constructing their own decisions.
Artificial intelligence changes that relationship. Visibility remains necessary. Increasingly, it is not sufficient.
As AI performs a growing share of the cognitive work connecting buyers with sellers, competitive advantage becomes progressively linked to participation within AI-mediated decision processes.
This represents a structural rather than merely technological change. The mechanisms through which markets allocate demand are evolving.
Several strategic predictions follow from the argument.
First, market visibility alone will become an increasingly incomplete source of competitive advantage. An organisation may remain highly visible in traditional channels while becoming less represented within AI-mediated decision environments. The prediction follows directly from the shift from information retrieval towards machine-assisted interpretation and evaluation.
Second, organisations that are consistently interpretable within AI-assisted decision environments are likely to gain structural advantages. This does not mean that AI will reward organisations according to a universal ranking system. Rather, where AI participates in decision-making, the ability of a system to form a coherent representation of an organisation becomes a prerequisite for meaningful evaluation.
Third, competition will increasingly shift upstream. Organisations will compete not merely to persuade buyers but to participate in the AI-mediated evaluation and selection processes that determine which alternatives reach human attention. This prediction follows from the causal sequence established throughout the article: discovery influences interpretation; interpretation enables evaluation; evaluation constrains selection.
Fourth, executives will increasingly manage two interconnected decision environments: one dominated by human judgement and another increasingly influenced by machine-assisted reasoning. The boundary between the two will remain fluid.
These are predictions rather than settled outcomes. The transition remains incomplete. Stanford's 2026 AI Index reports that organisational AI adoption reached 88% in 2025, while AI-agent deployment remained in the single digits across nearly all business functions. This suggests rapid adoption of AI alongside an earlier-stage transition towards more autonomous systems. (Stanford HAI, 2026)
The uncertainty therefore concerns the speed and extent of the transition, rather than whether AI is capable of participating in cognitive work.
Nor should the argument be interpreted as technological determinism. Human judgement remains indispensable wherever decisions involve ambiguity, negotiation, ethics, accountability or organisational context. AI does not eliminate competition. It changes the mechanisms through which competition unfolds.
This is the central strategic distinction. Markets have historically relied heavily on human judgement to transform information into decisions under conditions of uncertainty. Artificial intelligence increasingly performs part of that work. As that cognitive work becomes progressively shared between humans and intelligent systems, the mechanisms through which buyers and sellers connect begin to evolve.
Discovery becomes AI-mediated. Interpretability becomes a competitive requirement. Evaluation becomes increasingly machine-assisted. Selection becomes compressed. Distribution becomes increasingly AI-mediated.
Viewed individually, these developments can appear to be incremental improvements in search, recommendation, productivity or customer experience. Viewed together, they reveal something more significant. Artificial intelligence is becoming an active participant in the market's decision-making process.
That is why buying decisions are changing first. They are the earliest visible point at which a deeper change in market coordination becomes observable.
Previous technological revolutions primarily changed the movement of goods, people or information.
Artificial intelligence is beginning to change the movement of decisions.
The strategic consequence is therefore larger than the emergence of a new interface or channel. When a technology begins to participate in the cognitive mechanisms through which buyers discover, understand, evaluate and select organisations, it becomes part of the infrastructure through which demand is allocated. AI is moving in that direction.
The organisations that understand this shift will recognise that the question is no longer simply how technology can improve the way they operate. The more consequential question is how the market around them is beginning to operate differently.
Glossary: Market Coordination Mechanisms
Reference definitions for the terms used in this article.
- Discovery
- determines whether an organisation enters the buyer's field of awareness.
- Trust
- reduces uncertainty by providing signals that an organisation's claims and capabilities can be relied upon. (Akerlof, 1970)
- Interpretability
- determines whether the organisation can be understood accurately: what it offers, which problems it solves, who it serves and under what circumstances it is relevant.
- Evaluation
- compares available alternatives against the buyer's objective.
- Selection
- converts comparative judgement into commercial action.
- Distribution
- determines the environments through which buyers and sellers encounter one another.
- Competition
- emerges from the interaction of these mechanisms as organisations seek inclusion within the same decision processes.
Key Definitions
- Market coordination
- The function by which a market connects buyers seeking solutions with organisations capable of providing them. Coordination emerges through a connected set of mechanisms rather than a single event.
- AI-mediated market coordination
- Market coordination in which artificial intelligence performs part of the cognitive work — discovery, interpretation, comparison and recommendation — that historically connected buyers with sellers.
- Cognitive work (in markets)
- The reasoning required to transform available information into a commercial decision: identifying suppliers, interpreting evidence, assessing credibility and comparing alternatives.
Questions This Article Answers
How is AI changing market dynamics?
AI is changing the mechanisms through which markets allocate demand. Rather than only moving information faster, AI systems increasingly perform discovery, interpretation and evaluation on the buyer’s behalf. Because competition emerges from those mechanisms, changing who performs the cognitive work changes how markets distribute opportunity between organisations.
Why are buying decisions changing before anything else?
Buying decisions are not the underlying phenomenon; they are the earliest observable manifestation of a structural change in market coordination. Because decisions sit at the point where information becomes commercial action, any redistribution of cognitive work becomes visible there first — before it appears in market structure or competitive position.
What is an AI-led buyer journey?
A buying process in which AI systems perform part of the reasoning buyers once performed themselves: identifying candidate suppliers, interpreting what each organisation does, and comparing alternatives against a stated objective. The buyer begins with a set that has already undergone machine-assisted assessment rather than an open field.
Does AI replace human judgement in enterprise buying?
No. Strategic purchasing, investment decisions and complex procurement continue to depend on human expertise, organisational priorities and contextual understanding. What changes is where cognitive work occurs: AI increasingly shapes the decision environment within which human judgement is then exercised.
Why does interpretability become a competitive requirement?
Because an AI system must construct an understanding of an organisation before it can reason about that organisation’s suitability. Where a system cannot determine reliably what an organisation does, who it serves and how it differs from alternatives, meaningful evaluation becomes impossible and the organisation risks exclusion.
References
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About the Author
Nune Igityan is the founder of Kensai, an AI and growth advisory focused on how AI is reshaping buyer journeys, market dynamics and business growth. She previously held senior product marketing and growth roles at Google and Meta and advises organisations navigating AI-driven changes in discovery, decision-making and distribution.
How to Cite This Article
Igityan, N. (2026) How AI Is Reshaping Market Dynamics: Why Buying Decisions Are Changing First. Kensai. Available at: https://www.kensai.uk/research/how-ai-is-reshaping-market-dynamics/
