I originally wrote “Competing in the ’90s – Impact of Technology” for Managing Technology for Profit: A Small Business Guide while leading an internal Fortune 500 corporate venture team. Our mandate was to identify, evaluate and acquire emerging technologies and strategic business opportunities that could strengthen, extend or create new growth opportunities around the company’s core businesses.
More than three decades later, I thought it was time to revisit it.
This 2026 edition updates the original thinking for a world of AI, automation, digital platforms and accelerating technological change—while retaining the central entrepreneurial message.
IMPACT OF TECHNOLOGY
In the 1980s and 1990s, markets were opened by globalization, cheaper transport, better communications and offshore manufacturing. Geography, industry boundaries and long-term supplier relationships became weaker barriers to competition. Consumers gained greater choice and the rules of the game changed.
The first competitive wave was about price. Companies cut operating expenses, rationalized operations and suppliers, automated and moved production offshore. Manufacturing shifted toward lower-cost economies.
The second wave was about quality and productivity. Quality management, lean production and continuous improvement became management catch phrases. Employers sought innovative climates where employees could contribute ideas rather than merely follow instructions. Creativity became a valued commodity.
The third wave was about speed. Changing customer needs demanded shorter product cycles, faster response times, shorter payback periods and better informed workers. The internet connected markets and customers globally. Technology became a competitor in its own right.
By 2026 another wave has arrived.
Artificial intelligence, cloud computing, automation and digital platforms are reducing the cost of knowledge in much the same way that automation reduced the cost of manufacturing. Research that once took days can take hours. Software that required teams can sometimes be developed by a handful of people. Marketing material, product concepts, financial analysis, customer support and technical documentation can increasingly be produced or assisted by AI.
The scarce commodity is shifting from information to judgement.
The competitive question is no longer simply, “Who has the technology?”
Increasingly it is, “Who can use the technology better and faster?”
This distinction matters because AI is becoming widely available. When competitors have access to similar tools, the tool itself provides little protection. Competitive advantage must come from what surrounds it—proprietary knowledge, intellectual property, unique data, customer relationships, distribution, brand, specialist expertise and the ability to execute.
AI simultaneously lowers barriers to entry and raises the speed of competition.
A small company can now command resources that would once have required a much larger organization. But large companies can apply the same technology across enormous customer bases, datasets and distribution networks.
The small company must therefore use technology to multiply its strengths rather than imitate the large company.
Technology can still fence off market niches, but the fence has changed. Patents remain important, as do trademarks, copyright and trade secrets. Increasingly, however, the strongest protection may be a combination of intellectual property, proprietary data, customer knowledge, speed and continuous innovation.
The lesson is simple.
If competitors can buy the same technology tomorrow, build something around it that they cannot easily buy.
MANAGING IN THE FACE OF RAPID CHANGE
Business is subject to change. Change is brought about by recession, geopolitics, regulation, social innovation and technical innovation. Change creates new markets and service opportunities. It also reforms established industries by shaking out the weakest.
We need to understand the rules of the game to compete in such a climate—but increasingly there are no permanent rules.
Without rules we face risk, but we also face opportunity.
Preparing a competitive strategy in an emerging industry requires that we address uncertainty rather than pretend it does not exist. The ability to perceive coming trends and the flexibility to take advantage of them remain essential tools.
What has changed is the speed.
Strategic planning can no longer be an annual ritual based largely on what happened last year. Management must continually ask what has become technically possible, what has become cheaper, what customers are beginning to expect and what a new competitor could now do that was uneconomic twelve months ago.
In 2026 there are three major uncertainties to confront.
The first is technical uncertainty.
What product configuration is best? Which technology is most cost effective? Should we build, buy, license or partner? Which AI systems should we use? How quickly will today’s technology become obsolete?
Alternative products and technology routes must be evaluated against the risk to current business.
The second is strategic uncertainty.
What is the right distribution strategy? What should we manufacture ourselves and what should we outsource? How should the product be packaged, priced, marketed and serviced? What scale is economical? What customer problem are we really solving?
AI adds another question: should technology reduce our costs, improve our product, create an entirely new product—or enable a competitor to eliminate our product altogether?
The third is regulatory and institutional uncertainty.
AI, cybersecurity, privacy, intellectual property and data ownership are becoming management issues rather than matters left solely to lawyers or technical staff. The question is no longer merely what technology can do, but what we are legally and commercially prepared to allow it to do.
Technology creates opportunity, but unmanaged technology creates liability.
THE NEW LEARNING CURVE
Emerging industries have always been characterized by high initial costs followed by falling costs as production experience increases.
Electronic calculators, semiconductors, computers and telecommunications all demonstrated steep learning curves.
AI accelerates the principle.
Development costs can decline rapidly because software, research, design and analysis can increasingly be assisted by machines. Technology available only to sophisticated companies today may become an inexpensive service tomorrow.
This presents both opportunity and danger.
Do not assume that today’s expensive technical advantage will remain scarce.
The trick is to convert a temporary technological advantage into something durable before the technology becomes commonplace.
That may be a patent. It may be proprietary data. It may be a distribution agreement, regulatory approval, customer relationship, brand or accumulated know-how.
The emerging phase of an industry remains characterized by embryonic companies and spin-offs. AI encourages this phenomenon because small teams can now accomplish work that once required substantial organizations.
Therein lies the trap.
It has become easier to create a product. It has not necessarily become easier to create a business.
When everybody can build faster, customer access, trust and repeat business become more valuable.
The old problem remains: how do we turn the first-time buyer into the repeat customer?
BE THE HAMMER, NOT THE NAIL
To succeed in an emerging industry requires a company to be the hammer and not the nail.
The overriding plan should be to influence the structure of the industry rather than merely react to it.
Product specifications, intellectual property, pricing, distribution, technical standards and strategic partnerships can all help establish a strong long-term position.
But the product alone is rarely enough.
Success depends on consistent quality, staying ahead of copycats and presenting a credible front to suppliers, customers, regulators and the financial community.
Suppliers and distributors should still be courted early in the game. So should technology partners, data providers and key customers.
As the market grows, these relationships become assets.
In real estate they say the three primary factors are location, location, location.
In emerging industries the primary strategic factor remains: Timing, timing, timing.
Pioneering or early entry involves risk, but can offer otherwise unavailable advantages.
Early entry is appropriate when a company can establish a reputation as a pioneer, when a steep learning curve exists, when customer loyalty can be created, when proprietary data can accumulate and when finance, distribution or supply relationships can be secured.
Early entry is not appropriate when the product does not match the market, when customer education and regulatory costs are high, when formidable competition is approaching or when continuing technological development can make today’s investment obsolete.
With AI this last risk deserves particular attention.
A company can spend heavily solving a technical problem that a general-purpose AI system makes inexpensive six months later.
Being first is therefore not enough.
The objective is to be early enough to learn and late enough to avoid paying unnecessarily for yesterday’s technology.
FINANCING THE OPPORTUNITY
The trick remains to time financing needs to take advantage of investors’ enthusiasm for an emerging industry without becoming dependent upon it.
Technology fashions change. Capital markets change faster.
Prepare for high initial costs and for market barriers to fall more rapidly than expected. The market can go down faster than it rises.
This requires flexibility and sufficient capital to defend the turf while the business becomes established.
Money spent on technology should ultimately do one of five things: lower cost, increase revenue, improve the product, accelerate innovation or strengthen a competitive barrier.
If it does none of these, it may be technology looking for a business case.
AI productivity should not automatically be confused with competitive advantage.
If every competitor obtains the same productivity improvement, competition will eventually pass much of the saving to the customer through lower prices.
The objective is to convert productivity into advantage before productivity becomes a commodity.
MARKETING IS STILL THE GAME
Do not rely solely on a unique product or proprietary technology to create business awareness.
Technology does not sell itself. Indeed, AI makes this problem more acute.
The cost of producing words, images, advertisements and promotional material has collapsed. Customers consequently face more information, not less.
When content becomes abundant, attention and trust become scarce.
Marketing therefore remains central to the game.
Know the customer. Understand the problem. Communicate the benefit. Establish credibility. Make purchasing easy.
AI can help identify prospects, personalize communications and analyse customer behaviour, but it cannot rescue a product the market does not want.
A faster way of selling the wrong product is still the wrong strategy.
COPING WITH COMPETITORS
Coping with competitors can be difficult, both emotionally and financially.
The latecomer will try to fill the market niche we have created. The latecomer will learn from our development mistakes and may use newer technology at lower cost.
AI makes the latecomer’s job easier.
Consequently, a sustainable business cannot depend solely on being first.
If we have prudently courted financiers, suppliers, customers, distributors and technology partners early, we can concentrate resources on building company strength and developing the industry as a whole.
A bigger pie can still satisfy more appetites.
It may even serve our purpose to encourage competition by licensing technology, establishing standards or allowing complementary businesses to build around our product.
Licensing can recover valuable cash, open new markets, provide market intelligence and create additional product lines.
The objective is not necessarily to own everything.
It is to own or control something important.
COMPETING WITH AI
AI should be treated neither as magic nor as a threat to be ignored.
It is a tool for changing the economics of work.
The strategic question is where that change creates value.
Before investing, management should ask:
Does this solve an important customer problem?
Does AI materially improve cost, speed or quality?
What remains unique when competitors obtain the same AI capability?
Why is now the right time?
Can we learn faster than competitors can copy us?
These questions separate an interesting technology from a sustainable business.
Human creativity remains a valued commodity. If anything, it becomes more important.
AI can generate alternatives. It can analyse information, produce designs and propose answers.
Someone must still decide which question is worth asking, which answer can be trusted, which opportunity deserves capital and which risk should be taken.
The winning combination is therefore not man versus machine.
It is: human judgement + specialist knowledge + data + AI + execution.
History is littered with companies that paid the price for denying social and technological change.
It also contains companies that adopted new technology enthusiastically without ever discovering how to make money from it.
Neither resistance nor enthusiasm is a strategy.
The task of management is to recognize change early, evaluate it intelligently and act while an opportunity still exists.
Technology changes.
Markets change.
Competitive advantages disappear.
The company that learns and adapts faster than its competitors has the best chance of surviving the next wave.
Uncertainty, once understood and managed, remains the entrepreneur’s opportunity.