Investing in Artificial Intelligence
December 2017
Introduction
Artificial Intelligence (AI) is a burgeoning industry, generating over USD 5 bn in revenue in 2015, with industry experts predicting this to grow x60 to USD 300 bn by 2025. It is also expected that AI will disrupt many industries. Thus AI has been one of the hottest investment sectors of late. For instance, Intel recently spent USD 1.3 bn for its acquisition of Mobileye, a 'maker of sensors and cameras for computer-assisted and autonomous driving'. However, investing in AI isn't without peril and danger.
In order to determine how to maximise your investment in Artificial Intelligence, we will first review the following:
AI Investment Activity
AI Valuation and M&A Context
AI Growth Drivers and Added Value
AI Market Outlook
AI Challenges
AI Investment Activity
Overall Activity
AI has seen a sharp increase in investment in 2017, both in terms of volume and value.
Mergers & Acquisitions
AI M&A activity is up in 2017 H1.
The most active AI acquirers have been tech giants in the last 5 years.
The largest 2017 AI deal was Intel /Mobileye (USD 15.3 bn).
Traditional companies also invest in AI (e.g. John Deere / Blue River Tech. for USD 305 m).
Venture Capital Funding
VC investment in AI continued its record growth in 2017.
The top 100 startups have raised USD 3.8 bn since 2012.
62% of AI VC deals went to US startups in 2016.
Although VC funding is maturing, most AI VC deals are still small.
AI Unicorns span across industries (e.g. FS, healthcare, security, analytics, auto, software).
AI IPOs are rare (e.g. Veritone in May 2017).
Government Initiatives
China plans to lead the World in AI by 2030, and to generate USD 1.5 tn for the Chinese economy (across all AI-related fields).
Many developed countries (UK, UAE, Singapore, France, US) are also seeking to foster AI.
AI Valuation and M&A Context
AI Valuation
AI M&A transaction multiples are high:
EV/Sales = 5.3 x
EV/EBITDA = 39.7 x
P/employee ~ USD 9m
Global M&A Context
The global M&A activity remains buoyant
Above average M&A valuation levels persist
Private Equity acquirers face record-high multiples
Tech M&A Context
Tech M&As approach the heights of the year 2000
Valuation multiples for Tech targets are rising
Large cap deals drive the Tech M&A market
AI Growth Drivers and Added Value
AI Growth Drivers
Computing power and 'big data' are the main growth enablers of AI
Semiconductor chips are being optimised for AI, for example:
Nvidia: GPU for large-scale customers and for cryptocurrency-linked demand
Google: Tensor Processing Unit
Intel: NNP (Neural Network Processors)
Open source software (e.g. Google’s TensorFlow) accelerates research.
The US tech giants actively apply for AI patents.
The number of active investors in AI is increasing.
Algorithms have improved, and deep learning has been a breakthrough for AI.
AI attracts growing interest and expertise, and is benefiting from greater business focus.
AI complements technologies such as robotics, IoT, blockchain, and AR/VR.
AI Applications
AI is pervasive across nearly every industry. Examples of business applications include:
Healthcare: Drug Discovery, Cancer Cell Detection, Diabetic Grading, Patient Care
Autonomous Vehicles: Pedestrian Detection, Lane Tracking, Recognising Traffic Sign
Finance: Automatic Stock Market Trading, Fraud Detection
Retail: Personalised Shopping Assistance, Advertising, Marketing, Loyalty
Media: Advertising intelligence, Call center operations, Real-time translation, Gaming, Media management, Media creation
Telecoms / network operations: Lighter engineering, Predictive networks, Simplified trouble shooting, Operational efficiency
Telecoms / consumer: Predictive marketing, Value-added services
AI Added Value
AI can generate Return on Investment. For example, Netflix avoids subscription churn worth USD 1 bn in sales, through better search results.
AI could contribute USD 15.7 tn to the global economy by 2030, from increased productivity and consumption-side effects
All the world regions are set to benefit from AI, albeit at varying degrees:
Largest gains: North America and China will enhance their GDP by 14.5% and 26.1%, respectively
Significant gains: Northern Europe: 9.9%, Southern Europe: 11.5%, Developed Asia: 10.4%
Modest gains: Developing Countries: around 5%
AI Market Outlook
AI Market Forecast
The total AI market (software, hardware, services) could reach USD 300 bn by 2025.
Industry Outlook
Based on the number of VC deals, the hottest AI areas include Healthcare, Fintech and Insurance, and Commerce. Emerging AI Applications include Legal, Education and Media.
Financial Services, High Tech & Telecommunications are set to grow the fastest, based on a survey.
Medical Diagnostics, Search, and Sales & Marketing will generate 79% of the AI revenues over 2017-2025.
Technology Outlook
Deep learning, machine learning, and NLP are set to generate 79% of AI revenues over 2017-2025.
AI Challenges
AI Market Challenges
AI faces barriers to corporate adoption, such as cultural resistance, limited technology capabilities and talent, lack of leadership support, unclear business case, and security concerns.
Around one third of consumers are uncomfortable with AI.
AI presents societal risks, including:
Privacy/Ethics/Safety issues
Legal/Liability/Ownership issues
Unemployment
Negative impact on social interactions
Threat on humans (Artificial Super Intelligence)
AI Investment Challenges
Larger tech deals command higher premiums.
Only half of tech deals create value for the acquirer at announcement.
Tech M&A value creation depends on experience.
Trends and investments in AI are set by leading players and academia.
AI talent is scarce.
AI targets are expensive, and the most promising opportunities are captured by tech giants.
AI valuation is volatile (e.g. following its IPOs, Veritone’s shares have fallen from their peak).
Early-stage AI companies are difficult to assess.
Integrating and scaling AI companies often ends in failure.
AI Investment StrategY
Pre-deal Recommendations
Integrate your digital and your business strategy
Reinvent your business model
Obtain executive sponsorship
Create your business case
Assess your business readiness and create your change management plan
Carefully select your area of AI investment, for instance a/an...
Industry (e.g. fintech) or horizontal application (e.g. sales optimisation) where AI provides the most disruption
Segment where AI is bundled with key innovation (e.g. robotics for surveillance)
Long-term AI path (e.g. quantum computing), different from this of the Cloud players
Area with momentum (e.g. NLP)
Area with possible M&A exits (e.g. security)
Focus on early-stage startups
Search for AI companies around several tech hubs (beyond the Silicon Valley)
Establish a strong deal team with both M&A and technology skills
Develop a deal management and integration template
Deal Recommendations
Carefully assess your target using these criteria:
New possibilities aligned with strategy
Founder with vision & business solutions
Data strategy and access to internal & external data
AI technology & patents
AI Talent
Value the target based on its potential, rather than multiples
Follow a deal process tailored to the tech sector, acting fast and remaining flexible with regard to the deal structure
Post-Deal Recommendations
Integrate with a light touch (incubator/accelerator)
Build a portfolio of AI investments
Develop your corporate AI capability (recruit AI experts, train your staff, re-design your processes)
Foster a digital culture through change management
The full article is available here:
https://www.linkedin.com/pulse/how-maximise-your-investment-artificial-intelligence-piciocchi/