US venture capital deal value in artificial intelligence booms to $6 billion

06 September 2018

A new report from Drake Star Partners reveals that venture capital investment in the US AI industry has grown to $6 billion in 2017. Meanwhile, global investment in AI companies grew to over $12 billion, with heavy interest from tech corporations Google and Intel, and their related VC funds.

Artificial Intelligence is slated to revolutionize multiple facets of human society, from the way we get around (automated vehicles), how companies interact with customers (advanced chatbots), and how we work (machine learning factory robots and routine back office processes bots). There is already AI tech available that can do routine and repetitive tasks better than humans, and can learn and self-improve. But AI can go further than that. While AI can assist surgeons to do their jobs better today, there may be a future where super-precise surgical bots perform operations themselves. Artificial intelligence has the potential to replace more jobs than people expect, depending on the pace of technological advancement (and human reticence).

The revolutionary field is attracting the investment of heavy-hitting tech firms and VC funds who are looking to be on the vanguard of the productivity game changer. According to a new Artificial Intelligence Industry Update from global boutique investment bank Drake Star Partners, the global AI industry has received over $24 billion in investments over the past three years – with over half that value invested in 2017 alone. The US saw $6 billion in deal value in 2017, with a deal volume of 600. Investment in the US AI sector has strongly picked up its pace since 2012, when deal value was under $1 billion.US Venture activity in AIThe Drake Star report reveals that the most active VC funds in the space are Data Collective, Khosla Ventures, Intel Capital, New Enterprise Associates, Google Ventures, and Bloomberg Beta. Intel Capital has invested in (or acquired) dozens of AI firms, including Razer, CubeWorks, and Perfant, while Google Ventures has invested in firms ranging from Building Robotics to Zephyr Inc. Meanwhile, Bloomberg Beta has invested in firms like Deep Genomics and Aviso.

The most active corporate buyers in the space included tech heavyweights Google, Apple, Intel, IBM, Salesforce, and Facebook. In the past two years, Google bought Allmatter, Halli Labs, Kaggle, Dialogflow,, and Moodstocks; Apple acquired Regaind, Lattice, RealFace, tuplejump, Turi, and Emotient; Intel bought XPS; Saleforce bought Coolan, MetaMind, and TappingStone; and Facebook bought Dreambit and FacioMetrics.

Venture capital investment in AI is booming as the projected revenue of AI companies is set to skyrocket. The report estimates a dizzying compound annual growth rate of 39.5% from 2016 to 2025 for the global AI market. From a total global revenue of $4.82 billion last year, AI companies are expected to post revenues of $37.99 billion in 2022, and $89.85 billion in 2025.Project Revenue of AI companies, globally“As AI becomes more advanced and more accessible to consumers, its demand and revenue are expected to increase drastically,” stated the report, co-authored by Drake Star CEO Greg Bedrosian and AVP Lyle Finkler. “Technology is shifting where companies now utilize the AI technologies of machine learning, deep learning, or augmented reality. As AI becomes more mainstream, its cost goes down and, therefore, its accessibility to the broader marketplace increases.”

Adoption and awareness of AI is growing, though insider surveys indicate the technology is some distance away from human-level machine intelligence. As such, AI is being adopted in a multi-tiered approach, with different-level capabilities as they become available: a customer service chatbot is still far off from the goal of a human-level machine AI. The report combined a number of relevant surveys to give a rough guess of how far off the technology is from full-human intelligence, with the guesstimates of 2022 for 10% human level intelligence, 2040 for 50%, and 2075 for 90%.

A key reason why investment in AI is booming is because of its potentially massive implications on worldwide GDP and productivity. The Drake Star report projects that China will gain 26.1% GDP growth due to AI by 2030 (or $7 trillion in GDP), while North America will gain 14.5% (3.7 trillion in GDP).Impact of future AI on worldwide GDPs in 2030Inevitably, the question comes to how many jobs could be lost from AI technology. An OECD report projects that about 14% of jobs are easily automatable, accounting for about 13 million US jobs. On the other hand, Bain & Company estimates up to 25% lost jobs in the US by 2030 due to automation. Other consulting firms give rosier pictures, but really, it’s hard to predict how many jobs will be lost because analysts don’t accurately know how far or how fast the technology will advance. That’s why various consulting firm estimates are all over the place – perhaps partly influenced by whether they want to craft an optimistic narrative or not. These are the kind of projections, after all, that terrify people and cause anxious governments to ponder basic universal income.

As the AI industry matures, the Drake Star AI report offers a few trends to look out for. The firm expects more verticalization of AI – like specific applications for healthcare, energy, etc. – as investors increasingly seek out firms that offer direct applications for their markets. Furthermore, Deep AI companies will continue to be the most valued firms, as finding teams of PhD-level researchers will remain difficult.

Meanwhile, mobile devices will field consumer-facing AI – as the iPhone X will come equipped with hardware to power machine learning algorithms in their Face ID, Animoji, and augmented reality apps. Finally, the report expects AI applications in VR to become more publicized as the platforms Magic Leap and Oculus Rift are released this year.


Deloitte reveals new tool to measure social impact of corporate investments

27 February 2019

Accounting and consulting firm Deloitte has developed an advanced measurement tool to help corporations, governments, and stakeholders better determine the impact of corporate investments on various social measures.

People – especially millennials – are increasingly focused on the social impact companies make. As such, companies are keener to craft a company image that "cares," that genuinely supports causes because it is the right thing to do. The fact that it might boost revenue and increase brand loyalty, however, is a solid bonus.

In the wake of such information, Big Four firm Deloitte has released a machine learning-powered tool that helps measure the social impact of large corporate investments across more than 75 social areas, including education, housing, income and employment, and transportation.

"With the rise of the social enterprise – those organizations looking beyond revenue and profit to understand their impact on society – many of our clients are raising the profile of purpose-driven outcomes," said Janet Foutty, chair and chief executive officer, of Deloitte Consulting LLP. "The Social Impact Measurement Model (SIMM) enables our clients to understand if their investments will pay social dividends, providing value to companies, communities, and local governments."

Deloitte reveals new tool to measure social impact of corporate investments

When a large company previously company invested a great deal of money into a county build a widget factory, analysts typically examined surface level figures such as job creation and income to determine the initiative’s economic impact. Deloitte’s model quantifies the social impact of that investment over four years, illuminating how it may affect poverty, home ownership, and high school math scores.

While many might take a "ra-ra" attitude to any corporate investment, critics on the other side of the debate counter that it isn’t always rainbows and sunshine. Cities like Seattle and San Francisco have basically had their quality of life – especially in terms of living expenses – in part destroyed by massive tech industry expansion and investment.

Yes, the tech industry has created ultra-high-paying jobs and the indirect economic benefits which spring from them. But it’s also placed a large amount of pressure on housing, increasing rent and housing prices to laughable levels. In the meantime, neighborhoods have been blasted by gentrification, with old establishments pushed out by upscale resto-bars that cater to the rich, as the city takes on the form of a playground for the wealthy.

Meanwhile, the non-tech-elite toil at stagnating wage rates, pushed out of the city by the skyrocketing cost of living, commuting to low-skill jobs that soon won't exist because of the advancements in the tech industry.

The question is, does attracting tech investment wreck a town for the people that don’t have the niche skills required to take part in the digital dream? It’s not like opening a factory, where most anybody can jump in; instead, it might just bring in a bunch of well-heeled youths from elsewhere, who mess up the game for everyone else.

In any case, Deloitte’s SIMM can bring more data to that worthy public discussion. "Businesses make many corporate investments each year, some of which induce fierce bids by local governments and generate strong debate," Darin Buelow, principal of Deloitte Consulting LLP and real estate and location strategy practice leader, said. "The ability to estimate the social impacts of a capital investment allows citizens, corporations, economic development officials, and other stakeholders to bring data to the debate, better informing decisions and portraying long-term social outcomes that were previously unknown."

As such, the tool can help corporations guide decisions about what whether to make capital investment in the first place, while allowing policymakers to see how communities translate financial investments into social outcomes.

Different impacts

SIMM has already shed light on how investments in the same industry can have different impacts in different locations. For example, a half-million dollar investment in a rural wealthy county has less overall social impact than the same investment in a densely populated, wealthy county.

Similarly, investments in poor, urban counties can improve child poverty levels, and reading and math scores, while the same investment drives little to no change in child poverty and reading and math scores in poor, rural counties.That investment does decrease the adult poverty rate to a higher degree in poor, rural counties than poor, urban ones. When poverty rates are approximately equal, investments seem to help children more in densely populated areas, while helping adults more in rural areas.

Although it’s a helpful quantitative tool, Deloitte cautions that SIMM merely gives an estimate, and is only meant to supplement established information gathering methods and analyses in regards to capital planning and allocation. SIMM also doesn’t isolate an investment as the sole cause of changes in social measures, but it does “create a causal link between the investment and other contributing factors,” according to the consulting firm.