Artificial Intelligence: How you can use “deep tech” for your company

Artificial Intelligence: How you can use “deep tech” for your company

When scientists rushed to develop a vaccine against the SARS-CoV-2 coronavirus that causes COVID-19 in early 2020, it seemed like a really long road to go. The fastest vaccine ever developed was for mumps, back in the 1960s – a trial that lasted 48 months. But just nine months later, in December 2020, the American pharmaceutical giant Pfizer and a German deep-tech startup, BioNTech, had developed the first COVID-19 vaccine, thereby validating the use of the new technology of mRNA-based vaccines.

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

Like Pfizer and Moderna in the pharmaceutical industry, several corporations in other industries – such as Tesla in the automotive industry, Bayer in agrochemicals, BASF in specialty chemicals, Deere in agricultural engineering and Goodyear in the rubber industry – rely on deep technologies. Deep tech, as we call it, is the problem-oriented approach to tackling big, hairy, daredevil and nasty challenges by combining new physical technologies like advanced materials science with sophisticated digital technologies like AI and soon quantum computing.

Deep Tech is coming to the fore as companies urgently need to develop new products faster than before; to develop sustainable products and processes; and become more future-proof. Deep Tech can generate tremendous value and will offer companies new sources of advantage. In fact, deep tech will disrupt incumbents in almost every industry. This is because the products and processes resulting from these technologies will be transformative, creating new industries or fundamentally changing existing ones.

The first prototypes of Deep Tech-based products are already available. For example, the use of drones, 3D printers and syn-bio kits is increasing, while no-code/low-code tools are making AI more accessible. They open up more ways for companies to combine new technologies and catalyze more innovation. Not surprisingly, incubators and accelerators have sprung up around the world to facilitate their development. Today, not only are more deep tech startups being formed, but they are bringing successful innovations to market faster than ever before.

For CEOs of established companies, it is risky to rely on a wait-and-see strategy. They need to find ways to immediately realize the potential of deep tech before their organizations are disrupted by it – just as digital technologies and startups disrupted business not so long ago. However, unlike digital disruption, the physical-digital nature of deep tech presents an excellent opportunity for established companies 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 costly for physical products, by leveraging their engineering and production scaling expertise and granting market access. And since incumbents are already at the heart of global networks, they can also help circumvent government regulations and influence their suppliers and distributors to migrate to infrastructure that supports the new processes and products. This unleashes tremendous value, as the Pfizer-BioNTech case exemplifies.

Most established companies will find that deep tech initially presents two major challenges. First, it is not easy to identify or evaluate the business opportunities that new technologies will create. Second, it is equally difficult to develop and deploy deep tech-based solutions and applications, which usually require participation in and catalysis of collective actions with ecosystems. To overcome the dual challenges of deep tech, CEOs should consider three starting points.

throw back

Despite its sophistication, conventional technology prediction produces linear predictions and isolated thinking; it does not take into account how technologies are changing and converging. As a result, most forecasts underestimate the speed at which technologies will evolve and when companies will be able to take advantage of them. For this reason, companies should use “backcasting”, the method described by John Robinson of the University of Waterloo in the late 1980s.

Rather than tracking the development of many technologies, companies would be better off focusing first on the world’s biggest needs and most pressing problems, to identify the long-standing frictions and trade-offs that have prevented them from addressing them. Then they should define a desirable future in which those problems have been solved and work back to identify the technologies and combinations thereof that make solutions possible and commercially viable. Backcasting helps companies stay on top of both short-term and long-term technological changes, making it ideal for managing deep tech.

Anglo-American think tank Rethink X, for example, has used a backcasting-based technology disruption framework to highlight the impact of creating a sustainable world. The analysis suggests that technological changes in the energy, transport and food sectors, driven by a combination of just eight new technologies, could eliminate over 90% of net greenhouse gas emissions in 15 years. The same technologies will also make the cost of CO2 emissions affordable, so further breakthrough technologies may not be needed in the medium term.

measure change

When companies evaluate the business opportunities that deep technologies will open up, they should consider the scope of the changes they will bring. It is determined by the complexity of a technology and the company’s ability to scale solutions based on it. As Arnulf Grubler, director of the Austria-based International Institute for Applied Systems Analysis, and his co-authors argued six years ago, new technologies can bring about four levels of change. You can:

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

2. Improve an existing system. Colors enriched with nanomaterials and an AI-enabled smart home system, for example, can dramatically transform the home.

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

4. Transform a system-of-systems. Creating a purification technology that transforms current water supply and management systems will also transform how water-using sectors such as agriculture, alcohol, beverage, paper and sugar operate.

Finding out which of the four levels of change are likely to result will help companies better assess market sizes and growth paths. For example, when BCG recently estimated the market size of deep tech solutions in nine sustainability-related sectors, it found that while technological improvements in existing value chains would generate over $123 billion in additional revenues per year, those that led to systemic change , but generated 20 times more. Or up to $2.7 trillion a year.

cultivate ecosystems

Few companies already have all the technologies and skills they need to use deep tech. They must enlist the support of technology-related ecosystems ranging from academics and university departments to investors and governments to develop these competencies. The types of connections that result depend on the business opportunity as well as the maturity of the ecosystem.

Several types of collaborations are likely to emerge. Some established companies will obviously team up with startups to develop new products or processes, as Bayer did in 2017 and formed a joint venture with Ginkgo Bioworks to synthesize microbes that allow plants to make their own fertilizers. Others will orchestrate systemic change, which is what Hyundai Motor Group is trying to do in mobility by collaborating with several deep-tech startups. Still others may be focused on bringing deep technologies to maturity themselves, similar to the efforts of Sweden’s SSAB (formerly Swedish Steel), Vattenfal and Finland’s LKAB to scale up a sustainable steelmaking process that uses fossil-free electricity and green hydrogen to replace coking coal.

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Deep technology was impossible yesterday, is hardly feasible today, and may soon be so ubiquitous and impactful that life without it will be difficult to remember, points out Joshua Siegel of Michigan State University. The future will likely belong to companies that not only pursue deep tech, but invest in its development and drive its adoption by delving into ecosystems and forcing competitors to play the losing strategy of catching up.

Read others wealth Columns by François Candelon.

Francois Candelon is Managing Director and Senior Partner at BCG and Global Director of the BCG Henderson Institute.
Maxime Courtaux is a project manager at BCG and an ambassador at the BCG Henderson Institute.
Antoine Gourevitch 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 of the companies featured in this column are past or current customers of BCG.

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

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