AI Inside: how AI is shaping “softwarisation”

Note: this article derives from a broader article written by Duco Sickinghe and myself, where we look at some key trends that will shape the focus of the FortinoCapital VC and growth funds, see: Fortino Capital: Why we invest — and will be expanding — in B2B software-based start-ups | Fortino Capital

Sotfware eats the world- but softwarisation is changing shape

The “softwarisation” of our economies continues unabated since Marc Andreessen note 2011 “Why software is eating the world” interview with the Wall Street Journal. But beyond this recurring trend, we, at FortinoCapital, have also noticed that changes are underway that may further shape business environment, and reinforce our strategy to double down on software -based start ups.

1. The first change is that along hardware losing ground to software, more complex software now leads to a radical simplification trend in hardware. Tesla is a case in point- the revolution in the car industry is the shift towards smart mobility platform. But the new car hardware models are radically changing shape, from more than 50 in most traditional cars to just four components in the new Telsa models.

This software richness against simple UI-based design hardware means that software capabilities will only keep growing, putting aside incumbent companies without software skills, while offering the most capable start- and scale-ups a fantastic opportunity for making inroads in business.

2. Second, the world has finally scaled digitally. Covid-19, was a trigger- it boosts among distribution digitization, or led to a major workplace upgrades and further work automation. In fact, part of Fortino decision to invest in Peers was based on the support the company provides for workplace transition to automation by predicting the job-related skills employees will need to make this shift effective.

3. Another — and we believe crucial — trend is the rise of artificial intelligence. We know this “inside out” because of the sheer quality of the entrepreneurs and investments we have recently made in the likes of ReaQta, Oqton, or Zaion, to quote a few, that leverage AI to put themselves at the innovative edge of their respective industries.

Five AI tipping points

Why AI is at a tipping point is based on the following observations:

1. “AI radical economics” . Academic evidence is now solid about the material differences in productivity between AI-patenting and AI-virgin firms. This difference in the range of 5% a year, is about two- to three-times what has been observed in past technologies. Even better, recent studies suggest that the uplift in performance thanks to AI is especially favourable to small- and medium-sized enterprises — Fortino’s target market.

Second, the cost/performance of AI has significantly increased in the recent years. Consider, for instance, image recognition. Using ImageNet as a case study, image detection has grown from 80% accuracy in 2015 to 99% today, or nearly perfect and at least better than human eye. Meanwhile, machine learning training time has gone down from an average of about 6 minutes in Q4 of 2018 to less than one minute by Q1 2020. At the same time, the training cost for deep learning algorithms has gone down from more than $1,000 5 years ago to less than $10 today. Those are massive improvements, but the importance is that the performance/cost ratio makes AI more competitive than any other alternative.

2. “AI is a GPT” — A GPT is a Global Purpose Technology, or one that can affect all industries. In the recent past, most of successful AI cases were concentrated in a few sectors, such as high-tech services or service industries, such as finance, -and in a few firms, such as the FAANgs.

The last two years have made clear of the GPT power of AI. For instance, there have been significant breakthroughs in healthcare and pharmaceuticals, where they have had a dramatic effect on the economic structure of those sectors. In healthcare, diagnostics and smart automation have the potential to stop the sector’s secular inflation in our economies without restricting access to services. In pharmaceuticals, it has proven to have a major impact on drug innovation, let alone the time to market for vaccines.

AI is being absorbed by many companies with success. Manufacturing.net reports how Nissan has been running an AI Predictive maintenance platform for RUL prognosis and managed to reduce unplanned downtime by half . Coca-Cola In Asia has reported gain of more than 1 point of market share in a few months time by using AI based assortment reallocation techniques from mobile pictures of stores shelves .

Finally, AI is disruptive even to the FAANGs. In a sector like social media, ByTeDance successfully managed to enter and later dominate the global market for short videos, and this despite the prevalence of major players such as Facebook or Google’s YouTube.

3. “Europe is alive on the AI opportunity” — At present, the US and China each count about 30% of worldwide AI enterprises, with Europe only holding just half of that. But Europe isn’t sitting by idly: policy-wise, EU nation members have recently put together a synchronized plan that transcends each member country’s individual AI strategy. Furthermore, comparing Europe, not on the level of AI enterprises, but on refereed scientific publications, shows that Europe is much better placed than expected, and is on par with the US. The key is therefore that, for Europe, most of the boost is public institution-driven, as opposed to enterprise-driven.

Second, while it is known that Europe has more high-value-added B2B and manufacturing assets, Europe also has a comparative advantage in robotics and automation (24% of patents and firms). However, it also appears that Europe is pulling ahead of competition in hosting AI services (22%). This is pretty good news for Europe, as evolutionary economics teach us that technology starts at the infrastructure level, to then scale to services and bring the most profit and value.

Finally, the European AI talent pool is not only growing strong but is already seen as a clear advantage in the eyes of AI-tech giants such as Google, Microsoft, or IBM, who have all invested in their AI-based laboratories in Europe. Currently, large, US, AI-based firms have located 20% of their centres in Europe, for only about 1/3 in the US.

4. “AI based unicorns ” –Large tech firms are indeed holding a large concentration of AI resources , but as it so happens AI start-up funding has continued to expand aggressively, while we calculate that, by last year, 20–25% of unicorns were AI-based start-ups. This is a remarkable multiple relative to the share of start-ups being created, bearing in mind that AI technologies only saw their major breakthrough 3 to 5 years ago, or less than the average time it takes for a company to become a unicorn.

Also, as not all companies will have the capabilities to build and manage their AI factories, a market is being built upon the delivery of automatic AI solutions. This market may hinge upon large, open-source libraries such as the Google-powered TensorFlow, but the market is also being served by a broad array of successful start-ups, like DataBricks, Snorkel, or H20.ai.

And then there is the fact that Europe has a surprisingly large amount of young AI companies (up to 30%, and less than 5 years old). This contrasts with China, for instance, where barely 10% of their AI companies are new-born. This diversity of small firms may become a real asset to Europe in a few years when the ecosystem becomes more connected through the Digital Single Market.

5. “Software 2.0” — The final narrative is not about the success of AI, but more about its implications. At its most extreme, if AI is indeed pervasive and disruptive, can it also “eat” software, making a large part of software start-ups obsolete?One vision is the so-called “Software 2.0”, wherein data and neural network architecture machine learning models would replace human coding as the source code. But even if this trend is already somewhat visible, most Software 2.0 projects are yet to demonstrate consistent success.

Instead, we believe that AI will not (fully) replace full software making, but will act as a complement, to turbocharge better software — e.g., by automating code generation for some modules, or automated debugging and intelligent testing.

The new emerging world

Putting those changes together, software will continue to expand, but in different forms, among other fed by Artificial Intelligence. As said, we not onlyobserve this evlution, we are living it in the Fortino portfolio. Take, for example, ReaQta, who specializes in Cybersecurity and named as a Gartner Cool Vendor for their innovative AI/Maching Learning approach. Or there’s Oqton, recently acquired by 3D Systems, specifically for their AI approach to manufacturing. These companies demonstrate how broadly AI can already be applied.

In general, AI is here to say, and paraphrasing Julie Sweet, Chair and Chief Executive Officer of Accenture , we also believe that in this world, “cloud is the enabler; data is the driver; and A.I. is the differentiator” of business value.

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Ceo Machaon; Advisor UN/ FortinoCapital/Antler, retired from McKinsey, senior partner/leader McKinsey Global Institute, Chair Management University Brussels

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Jacques Bughin

Jacques Bughin

Ceo Machaon; Advisor UN/ FortinoCapital/Antler, retired from McKinsey, senior partner/leader McKinsey Global Institute, Chair Management University Brussels

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