Artificial Intelligence (AI) has usurped cost-of-living as the dominant topic in society, the marketplace and the economy.
And now, in their latest incarnation, AI shopping intelligence and technology are marginalising consumers' direct presence, roles, and influence.
A small but increasing segment is evolving in the US. Consumers are briefing and authorising artificial intelligence to search, find, engage, purchase from, and arrange delivery for products, services and applications.
However, there are notable limitations and pushbacks.
In general, consumers enjoy and, in many instances, prefer visiting bricks and mortar stores, interacting with frontline service providers and touching, smelling, and personally selecting specific purchase items.
What they dislike most is waiting in queues on the phone, online, and at premises. These queues can last hours with little prospect or guarantee of success in transacting a purchase.
Of particular relevance to AI shopping agencies (or agentic purchasing) are tickets to major events such as Taylor Swift concerts, NRL State of Origin matches, and Formula 1 racing.
Time-specific and limited opportunities, including Black Friday sales, Click Frenzy offerings, Cyber Monday discounts, and Boxing Day discounts, also have relevance, potential application, and advantages for an AI shopping agency.
Consumers can nominate specifics, including price ranges, models, brands, style, colour, dates, seating locations, and prioritised value packages.
Accordingly, AI agentic purchasing is more relevant to non-discriminatory packaged goods than to subjective, emotive, and nuanced selected fashion, stylistic, and fresh food options. Red is not red.
Ask Ferrari!
Better values
At present, AI agent sales represent less than three per cent of the market share in most categories.
The concept is limited in terms of awareness, acceptance, and preference.
Moreover, time has value for some, but not all. The bigger platforms, Amazon, Google, and TikTok, have the capacity but are reluctant to promote the offering lest they lose control of supply chains.
Larger global, national, and regional retail groups have been reluctant to embrace the principles and capitalise on the opportunities. Their algorithms can’t interact with and conclude transactions with many AI agent contacts.
Throughout Australia, Europe, and the US, established brick-and-mortar retail operations are sensitive to, and fearful of evolving into figurative fulfilment centres in which direct contact with their customers is restricted, limited or non-existent.
In such cases, repeat business recommendations, referrals, advocacy, and lifetime values will be redundant. Exposure to the prospects of leakage, shrinkage, and obsolescence is daunting.
Another day, another use
As I’ve written about before, it’s easy to get caught in the rush of Artificial Intelligence, and it comes with consequences.
Enhanced efficiency, effectiveness and productivity of innovations, technologies and disruptive processes may not result in better outcomes, advantages, benefits and rewards for customers and businesses. They can profoundly impact morale, cohesion, job security, employee attrition rates, customer service, and service delivery.
Skill gaps become evident rapidly, and internal and external satisfaction levels can decline.
Therefore, installing innovations and change is only an initial phase. Ensuring and optimising ‘fit’ may require attention, time, and resources to facilitate, install and support changes in structures, systems, processes, and skill sets.
AI works best from a broad existing database. Original and unprecedented thoughts, texts, expressions, responses, and actions have severely restricted scopes.
AI is fundamentally a tool that complements existing human, systemic, and structural resources. It does not and should not be employed to replace them. Operating in or from a void is hollow.
However, it comes with inherent costs, strengths, weaknesses, limitations, and needs. Each phase and step needs to be explored, mined, refined, and defined before acquisition, introduction, implementation, and operation.
AI shopping agents are another example of the possible uses of artificial intelligence that are emerging. Many of the foreseen consequences and costs for the current and potential participants are not quantifiable and represent existential risks for some.
A fundamental issue extends beyond the content and capacity of artificial intelligence. That is the context in which AI agencies fit in the business models of countless, differing, and, in many cases, long-established entities.
In all probability, this will be another case study in which capital outlays in the capacity for AI shopping agency (agentic purchase) will not be matched with investments in internal capabilities.
The potential will never be fully realised because of existing philosophies, cultures, purposes, practices, and people.
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