Artificial Intelligence: How to Put Deep Tech to Work for Your Business

Artificial Intelligence: How to Put Deep Tech to Work for Your Business

In early 2020, when scientists raced to develop a vaccine against the SARS-CoV-2 coronavirus that causes COVID-19, it seemed like a really long shot. The fastest vaccine ever developed was for mumps in the 1960s, an effort that took 48 months. Yet, just nine months later, in December 2020, US pharmaceutical giant Pfizer and German deep-tech startup, BioNTech, developed the first vaccine against COVID-19, validating the use of new mRNA-based vaccine technology.

The first studies on DNA vaccines began 25 years ago, and the science of RNA vaccines has also been developing for more than 15 years. One result was mRNA technology, which required the convergence of advances in synthetic biology, nanotechnology, and artificial intelligence and transformed the science—and business—of vaccines. Pfizer generated nearly $37 billion in sales from the COVID-19 vaccine last year, making it one of the most profitable products in the company’s history.

Like Pfizer and Moderna in the pharmaceutical sector, several corporations in other industries—such as Tesla in automobiles, Bayer in agrochemicals, BASF in specialty chemicals, Deere in agricultural machinery, and Goodyear in rubber—rely on deep technology. Deep Tech, as we call it, is a problem-oriented approach to tackling big, hairy, audacious and wicked challenges by combining new physical technologies, such as advanced materials sciences, with sophisticated digital technologies, such as AI and soon, quantum computing.

Deep Tech is coming to the fore because of the pressing need for businesses to develop new products faster than before; to develop sustainable products and processes; and become more future-proof. Deep Tech can generate enormous value and will provide companies with new sources of advantage. In fact, Deep Tech will disrupt existing companies in almost every industry. This is because the products and processes that will result from these technologies will be transformational, creating new industries or fundamentally changing existing ones.

Early prototypes of Deep Tech-based products are now available. For example, the use of drones, 3-D printers, and syn-bio kits is on the rise, while No Code / Low Code tools are making AI more accessible. They open up more avenues through which companies can combine emerging technologies and catalyze more innovation. Not surprisingly, incubators and accelerators have sprung up around the world to facilitate their development. Not only are more Deep Tech startups being created these days, but they are launching successful innovations faster than before.

It is risky for incumbents’ CEOs to rely on a wait-and-see strategy. They need to figure out ways to take advantage of Deep Tech’s potential now, before their organizations are disrupted by it – just as digital technology and startups disrupted businesses not so long ago. Unlike digital disruption, however, the physical and digital nature of Deep Tech provides a golden opportunity for incumbents to shape the evolution of these technologies and use them to their advantage.

Established giants can help Deep Tech startups scale their products, which can be particularly complex and expensive for physical products, by leveraging their expertise in engineering and manufacturing scale and by providing market access. And since incumbents are now at the center of global networks, they can also help navigate government regulations and influence their suppliers and distributors to move to infrastructure that will support new processes and products. This will unlock enormous value, as exemplified by the case of Pfizer-BioNTech.

Most incumbents will find that Deep Tech initially poses two serious challenges. First, it is not easy to notice or appreciate the business opportunities that new technologies will create. Second, it is equally difficult to develop and implement solutions and applications based on Deep Tech, which usually requires participation and catalyzing collective action with ecosystems. To address the dual challenge of Deep Tech, CEOs should keep three starting points in mind.


Despite its complexity, conventional technology forecasting produces linear predictions and isolated thinking; it does not account for how technologies change and converge. As a result, most forecasts underestimate the speed at which technologies are developing and when businesses will be able to use them. That’s why companies should use “backcasting,” the method outlined by John Robinson of the University of Waterloo in the late 1980s.

Rather than tracking the development of many technologies, business would do better to start by focusing on the world’s biggest needs and pressing problems to identify the long-standing frictions and trade-offs that have prevented it from addressing them until now. They must then define a desired future in which these problems are solved and work backwards to identify the technologies and combinations of them that will make the solutions possible and commercially feasible. Backcasting helps companies deal with both short- and long-term technological changes, making it ideal for managing Deep Tech.

The Anglo-American think tank Rethink X, for example, uses a technology disruption framework based on hindsight to highlight the implications of creating a sustainable world. The analysis suggests that technological changes taking place in the energy, transportation and food sectors, led by a combination of just eight emerging technologies, could eliminate more than 90% of net greenhouse gas emissions in 15 years. The same technologies will also make the cost of sequestering carbon affordable, so in the medium term more revolutionary technologies may not be needed.

Change measurements

When companies assess the business opportunities that deep technologies will open, they must consider the scope of the changes they will bring. It will be determined by the complexity of a technology and the ability of businesses to scale solutions based on it. As Arnulf Grubler, head of the Austria-based International Institute for Applied Systems Analysis, and his co-authors argued six years ago, new technologies can lead to four levels of change. They can:

1. Improve an existing product. For example, sustainable biodegradable plastic can replace conventional plastic packaging.

2. Improve an existing system. Paints inspired by nanomaterials and an AI-powered smart home system could, for example, dramatically change homes.

3. Transform a system. The development of the ecosystem for hydrogen-powered cars, from hydrogen production to gas stations, can transform urban mobility.

4. Transform a system of systems. The creation of treatment technology that transforms current water supply and management systems will also change the operation of water-consuming sectors such as agriculture, alcohol, beverages, paper and sugar.

Determining which of the four levels of change is likely to result will help companies better assess market sizes as well as growth trajectories. When BCG recently estimated the market size of Deep Tech solutions in nine sustainability-related sectors, for example, it found that while technological improvements in existing value chains would generate more than $123 billion in additional revenue annually, those that led to systemic changes , will generate 20 times more. Or as much as $2.7 trillion a year.

Cultivating ecosystems

Few companies already have all the necessary technologies and capabilities to implement Deep Tech. They must gain the support of technology-related ecosystems that extend from academia and university departments to investors and governments to develop these competencies. The types of connections that result will depend on the business opportunity as well as the maturity of the ecosystem.

Several types of cooperation are likely to form. Some incumbents will apparently join startups to develop new products or processes, as Bayer did in 2017, forming a joint venture with Ginkgo Bioworks to synthesize microbes that would allow plants to produce their own fertilizers. Others will orchestrate systemic change, which is what Hyundai Motor Group is trying to do in mobility by working with several Deep Tech startups. Still others may focus on nurturing deep technologies to maturity, similar to efforts by Sweden’s SSAB (formerly Swedish Steel), Vattenfal and Finland’s LKAB to scale a sustainable steelmaking process in which fossil-free electricity and green hydrogen replace coking coal.


A deep technology was impossible yesterday, is barely feasible today, and could soon become so pervasive and impactful that it will be hard to remember life without it, says Joshua Siegel of Michigan State University. The future is likely to belong to companies that not only track Deep Tech, but invest in its development and drive its adoption by engaging with ecosystems, forcing rivals to play the losing strategy of catch-up.

Read others Condition columns by François Candelon.

Francois Candelon is managing director and senior partner at BCG and global director of the BCG Henderson Institute.
Maxime Courteau is a project manager at BCG and an ambassador at the BCG Henderson Institute.
Antoine Gurevich is a managing director and senior partner at BCG.
John Paschkewitz is a partner and associate director at BCG.
Vinit Patel is a project manager at BCG and an ambassador at the BCG Henderson Institute.

Some companies mentioned in this column are past or current clients of BCG.

The opinions expressed in comments are solely the views of their authors and do not necessarily reflect the opinions and beliefs of Fortune.

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