Technology advances quickly, but consumer expectations rise even faster. People are no longer satisfied with tools that simply perform tasks. The new frontier is services that can anticipate and facilitate what comes next, whether it’s dreaming up the perfect destination wedding or just creating the menu for Taco Night. 

Soon this future will be upon us. Today's siloed apps and infrastructure are about to converge into personal mini-ecosystems. A new "smart fabric," woven from predictive intelligence and accessed through smart agents acting on behalf of individual users, will work across environments such as smartphones, wearables, voice, glasses, and emerging interfaces.

In simpler terms, the App Economy, which has been the dominant force in customer engagement for the last 15 years, is giving way to an era we call the Assistance Economy: a new model in which services know the user and show up “as they need them, when they need them” — at the point of demand — rather than requiring users to toggle between disconnected tools.

Companies that make these seamless connections possible will be the big winners. We project the Assistance Economy to enable more than $1.5 trillion in market value by 2029, based in part on our assessment of the economic potential of markets where agentic assistance is likely to deliver significant improvement in customer operations, marketing, and sales.

No one has a crystal ball on the timing of this transformation, but the pace of adoption of other breakthrough innovations suggests it’s reasonable to expect it within years, not decades. That means the time to invest and experiment is now — and some have already started.

How predictive AI and Assistance Economy can boost customer engagement

What does a smart fabric look like? Think of it like this: In the next few years, a layer of ambient “seers” will sense a consumer’s needs across ecosystems. The seers will be complemented by a layer of “doers” that will deliver immediate, curated solutions for any transaction or other activity a consumer chooses to engage in. Ultimately, consumers will be able to accomplish more, in less time, than they can in today’s hived-off App Economy.

Consider a person who is watching a cooking video hosted by their favorite influencer and who wants to give the recipe and cookware a try. Traditionally, this would require repeated taps between the social media app and a notes app to jot down the ingredients, then manually inputting the shopping list into a grocery app and scouring shopping sites for the best price on the pots and pans.

As the Assistance Economy takes hold, the same person might be able to watch the video and, with a spoken command, empower an agent to download the recipe to a cooking app, send part of the grocery list on to a grocery website, send the other part to a retailer to be procured using an exclusively sourced promotion, have the cookware ordered from the retailer with the best price, and schedule everything for same-day delivery.

To make all that possible, the smart fabric sorts through the relevant partners and manages transactions and logistics, enabled by the trusted agent working across what today is a fragmented system of disconnected apps and experiences.  

The megatrends and intelligent agents driving commercial success

The assistance concept is accelerating past the early adoption stage. Megatrends such as the rise of intelligent agents and ambient problem-solving, contextual advertising, and social shopping with micro-influencers are all well-established indicators of this broader shift. Comfort with agent empowerment is also strong, with over a quarter of the global population using a voice assistant this year, according to Google.

Market dynamics also are evolving. Organizations of all stripes are developing use cases for artificial intelligence (AI), but none (including among Big Tech) has yet managed to own or even orchestrate the full ecosystem.

New customer insights are playing a role as well. People are busier than ever, and appreciate curated offerings with less searching and quicker decision-making. An extension of this preference is a shift from user trust through marketed promotion to user trust from direct influence. It’s instructive, for instance, that TikTok’s shop is now the fastest-growing social commerce site in the world.

Using predictive AI as a personal assistant — the rise of smart fabrics

As smart fabric enablement improves, assistance use cases will increase in number and depth.

A good illustration is bill payment. Initially, assistance might look like a command and response function, where a user tells a doer to take care of a phone bill they forgot to pay. As the doer’s intelligence and awareness grow, it might nudge the user to pay the phone bill as they pass their mobile carrier’s store.

In an advanced stage, the doer is empowered to pay all the user’s bills, choosing payment methods that maximize benefits, while always ensuring the user reserves the right to course correct these decisions afterward. In this final form, a consortium of seers and doers will weave through the user’s smart fabric, optimizing every transaction and expense decision toward the outcome best aligned to the user’s lifestyle requirements.  

The travel e-commerce market, estimated at $3 trillion by Euromonitor, is another potential application. An assistance layer could recognize all of a user’s preferences that sit across their many travel apps. As the traveler provides a simple request — for example, “Take me on a Colorado ski trip for three days with my daughter over her spring break, spending no more than $5,000” — the assistance layer turns it into a neatly sorted travel folio that houses tickets, schedules, and passes, and optimizes reward program benefits to deliver the most value for the trip. Using predictive AI, the assistance seers and doers could plan a full itinerary of dining, relaxation, downtime, local transportation, and nice-to-have experiences.

Many other consumer needs lend themselves to the Assistance Economy, from healthcare (streamlining insurance claim management, optimizing health savings accounts) to education (finding a tutor, facilitating pursuits a school doesn’t offer) and beyond.

In all of these cases, the seer becomes smarter with every doer interaction, and over time the consumer experiences more of what they want and less of what they don’t. The more convenience delivered, the more loyalty created. 

The future of e-commerce with AI and the assistance economy

Short-term hurdles will make the path to full realization of the Assistance Economy less than linear.  

First, full assistance won’t be tethered to smartphone devices. As this year’s CES proved, more engagement interfaces beyond the phone are on the rise, but achieving screen separation will require a considerable behavior shift over the next three to five years.   

An additional barrier will be the willingness of companies to truly collaborate in an assistance-led ecosystem. The power of assistance comes from its ability to work comprehensively across a customer’s preferred brands and services. While there are some early indicators of what a true cross-brand ecosystem might look like — the money manager Snoop is just one example — initially we expect to see most companies follow the current “own the customer” strategy.

Companies can pursue a range of potentially lucrative avenues in the Assistance Economy. They might opt to become the orchestrator of an ecosystem, or a component supplier that offers specialized solutions addressing specific points of demand across multiple ecosystems — or something else altogether. In part two of our exploration of the emerging Assistance Economy, we will drill down into the specific roles companies can play as this new era unfolds.