T h e F u t u r e o f A I

families, ubiquitous intelligent access (push and pull) toinformation we need, flexible planning of our businessand leisure schedules, seamless business integration ofdifferent organizations, to name only a few possibilities.

Some of those dreams aren’t new—for example, theintelligent car. Others are recent—for example, thoserelated to accessing and processing the huge amount ofinformation on the Internet. From a technological view-point, there thus seems to be a great future for AI technol-ogy making its way into business and society.

The long road to marketWhat can we do to make this happen (and forget about

the AI winter)? The main challenges AI faces include tech-nical maturity, end-user acceptance, and the capacity toinnovate in business and society. With regard to innova-tion, (AI) researchers too often think the main challenge isto develop a working prototype—once that’s done, the restis easy. Nothing is less true; once you have a compellingprototype, the real work starts.

The road from a prototype to a successful product in themainstream market is long and winding, with many mile-stones. This road has been studied by economists and mar-keting professionals and walked by many of the successfulcompanies that developed from a specific technology. Un-fortunately, most AI researchers aren’t so familiar withthis road, and we all know the result. Many interesting AIprototypes and technologies never make it to the main-stream market and society. This is not because the tech-nology isn’t good enough but because we don’t know whatroad to walk and how to walk it.

Two helpful roadmapsTwo important, well-known concepts illustrate the road

from technology to mainstream market: the innovation

funnel1 and the technology adoption life cycle.2 The inno-vation funnel (see figure 1a) models how ideas becomeproducts. Having ideas is easy, turning them into concreteproposals is a bit more difficult, transforming that into aworking prototype is much harder, and commercializingthe software is a completely different story. Few ideas makeit to commercialization and end up in a new product, ser-vice, or even company. A consequence of the innovationfunnel is that as you move from idea to results, you needincreasingly more investment. Having an idea is cheap;commercializing a software product or service might in-volve millions of dollars.

However, having a commercial product, regardless of howgood it is, isn’t enough for success in the market. Accordingto the technology adoption life cycle (see figure 1b), there’sno such thing as “the” market; rather, there are different typesof markets, each with different customers that you must ad-dress in a specific manner.

The first stage is the innovators: techies (alpha and betatesters), who use technology for technology’s sake. Nextcome the early adopters: organizations that use new tech-nology not for its own sake but to achieve a breakthroughin their business or in society. These organizations usuallyhave ambitious decision makers who dream of such a break-through and believe that the new technology could makethis dream come true. The third stage is the early majority:clients who buy new technology only if

• it has been proven to work,• it provides a real business benefit,• it involves no risks,• full support is in place, and• the total cost of ownership is known and acceptable.

The final stage is the late majority, who buy the technologyonly if not buying it will harm their business. The technol-ogy’s real impact in business and society occurs in the main-stream market (the early and late majorities).

In addition, a “chasm” exists between the early adoptersand the early majority. Most technology products and com-panies that make it to the early adopters never manage to

I t’s easy to imagine a bright future for AI. A car that we

can speak to and that knows who we are (“let’s go home,

but first we do our weekly shopping”), homes where elec-

trical appliances communicate with each other and with

AI’s Future: Innovating inBusiness and Society

V. Richard Benjamins, Intelligent Software Components (iSOCO)

72 1541-1672/06/$20.00 © 2006 IEEE IEEE INTELLIGENT SYSTEMSPublished by the IEEE Computer Society

cross the chasm to the mainstream market.According to some people, this is whathappened with expert systems and neuralnetworks. Both are AI technologies thatencountered some commercial interest butnever made it to the mainstream market.

AI technology’s capacity to innovate inbusiness and society is key to making theleap from techies to the mainstream mar-ket. However, this capacity by itself isn’tsufficient. Technology users in general areexpecting increasingly more from the sys-tems or artifacts with which they interact.Such expectations include ambient intelli-gence, cognition, and interaction throughnatural language speech. Users are the“clients” of technologies, so technologyshould serve them according to their pre-vailing standards. Technology should also3

• be reliable,• have adequate response capacity,• make users feel important,• be “empathetic” (to give the user the

perception that the system understandsthe user’s point of view), and

• be competent.

All those requirements still form a real chal-lenge for AI, today and in the future.

References1. S.M. Dunphy, P.R. Herbig, and M.E. Howes.

“The Innovation Funnel,” Technological Fore-

casting and Social Change, vol. 53, no. 3,1996, pp. 279–292.

2. G.A. Moore, Crossing the Chasm, Harper-Collins, 1991.

3. L. Ford, D. McNair, and B. Perry, ExceptionalCustomer Service: Going beyond Your GoodService to Exceed the Customer’s Expecta-tion, Adams Media, 2001.

MAY/JUNE 2006 www.computer.org/intelligent 73

Results

Product/license

Technology push Market pull

New service

Spin-off/new market

PrototypeProposalIdea Commercialization

LaggardsEarlymajority

Earlyadopters

Innovators Latemajority

(b)(a)

Figure 1. Two well-known concepts that illustrate the road from technology to mainstream market: (a) the innovation funnel and(b) the technology adoption life cycle.

V. Richard Benja-mins is the directorof Innovation andR&D at IntelligentSoftware Compo-nents (iSOCO) inMadrid. Contacthim at rbenjamins@isoco.com.

http://www.computer.org/intelligent/subscribe

IEEE

SUBSCRIBE ONLINE AT

Peer-reviewedarticles

Expert departments

Thought-provokingeditorial

The #1 magazine inArtificial Intelligence