2019 Investment outlook - Technology

Artificial intelligence and the data wars

The cat is out of the bag

Artificial intelligence (AI) applications are likely to have a profound impact on businesses, markets, and global economies in 2019 and beyond. At the micro level, machine learning and the vast (and growing) amounts of underlying data should continue to improve client experiences through predictive analytics and personalization. Business leaders across all industries are supplementing their existing analytical processes with new data sources to make decisions with higher conviction. Within capital markets, the prodigious amounts of available data create the potential to discover new factors and variables in financial modeling. At the most macro level, AI can potentially lead to positive economic growth through a more efficient labor force and cross‐border commerce.

McKinsey data suggest that AI adoption could raise global gross domestic product (GDP) by as much as $13 trillion by 2030.¹ The amount of data produced continues to increase exponentially. In 2019, we expect companies will continue to dedicate significant resources to analyzing and exploring how their data can be turned into meaningful insights and drivers of revenue.

The difficulty with artificial intelligence and meaningful machine learning is that it relies on data as fuel. Perhaps the phrase “data is the new oil” is more significant now. Additionally, like oil, data needs to be refined to be useful in most circumstances. It needs to be collected, cleaned and distributed to provide actionable insights;, the biggest differentiator in the analogy is that minerals are finite whereas data is seemingly infinite. 2.5 quintillion bytes of data are created every day— that’s a 1 followed by 18 zeros— and the rate continues to increase.² Unsurprisingly, successfully building and improving data strategies requires a special skill set that is in high demand. The push for companies to embed AI throughout the fabric of their operations creates a need to first hire and then increase the productivity of their resident data scientists. Interestingly, while much of this work today is only available to data specialists, Gartner predicts that by 2020, more than 40% of data science tasks will be automated. Ironically, as data technology advances, data scientists are building technologies that perform similar work to their most sought after skills, effectively bringing disruption upon themselves.

Minutes Spent Using a Smart Speaker

Edge computing and the connected world

We believe that 2019 will bring a continuation of the “smart,” immersive human experience. The combination of autonomous things, smart spaces, digital workplaces, and smart cities will continue to blur the lines between the physical and the digital world. As systems become increasingly connected, various devices and spaces can coordinate and share data, resulting in a more seamless user experience. At a minimum, we expect the use of digital assistants in the home and workplace to continue rising, as voice‐enabled devices and screens proliferate.

Within the autonomous vehicle realm, there are still advances to be made in testing the reliability and safety of the computer vision and sensors that function as a vehicle’s “brain.” While much of the focus has been on personal vehicles, we believe there will be significant developments in autonomous freight, aerial taxis, and emergency vertical takeoff and landing (VTOL) vessels.

Of note, much of this connectivity requires edge‐computing capabilities. Edge computing refers to performing computational and processing operations at the source of the data, or at the “edges” of the network. Edge computing offers benefits in reduced latency, tighter security and privacy with Internet of Things (IoT) devices— Internet connectivity embedded in everyday objects, enabling them to send and receive data. It also offers improved bandwidth savings.³ Edge computing is starting to find adoption and grow in complexity, causing many businesses to reimagine their network strategies based on the efficiencies gained from marrying their cloud and edge computing strategies.

Blockchain and token economics

The past two years (2017 and 2018) marked an uptick in awareness and adoption of Bitcoin and Blockchain, respectively. Companies decided there was merit to combining the ideas of cryptographically secure transactions and distributed ledger technology to enhance transparency, accountability and security. Due to the potential high disruptive value of cryptocurrencies and blockchain, we expect 2019 will be a year of execution and the beginning of serious moves towards token economics. The questions currently being asked by businesses revolve around “how can we apply the fundamentals of these nascent technologies to real‐world use cases to unlock value and drive returns?”

In relation to blockchain, we expect to see companies bring proofs of concepts into production in 2019 across industries and sectors. We see this trend being led by focused applications with marked adoption in supply chain and logistics. Given the fact that the “business value‐add” of blockchain is predicted to be $3.1 trillion by 2030⁴, companies are eager to implement the technology. That said, network adoption is necessary for many blockchain models to work. In 2019, we’ll continue to see a wide dispersion when we survey the degree to which companies are implementing blockchain solutions.

As we consider the full potential of blockchain, traditional market economics will be brought into question as existing assets, both physical and financial, are tokenized. The birth of new asset classes and structures, new mechanisms for investing, new marketplaces and new secondary trading dynamics will give rise to the token economy. For example, Invesco is particularly interested in the tokenization of real estate, as it can offer the potential for lower investment minimums and a more liquid secondary market. We expect that in 2019, businesses (especially within financial services) will be considering their strategic value in the token economy. We expect to see a ramp‐up of companies experimenting with the tokenization of real assets and digital distribution. Similar to the phenomenon we saw with roboadvisors, we predict the adoption of tokenization will begin with younger, more digital‐friendly generations; however, we believe broader disruption is on the horizon.

Innovation labs and location strategy

Last, but certainly not least, is something we briefly touched on earlier — the battle for talent in the aforementioned technologies. While “innovation labs” have been in the spotlight for a while, we believe more companies will continue to invest in innovation spaces and facilities that better support emerging technologies to drive their long‐term strategic goals. While opening a new regional office in a hot market for key skills or renovating an entire existing office building may require significant capital expenditures, the potential returns are immense. Innovation spaces can attract diverse talent with the desire to work creatively, collaboratively and at speed. Furthermore, many of these innovation labs are located within ecosystems that offer the ability to create communities, facilitate collaboration with external partners and enable spontaneous encounters with innovators. Co‐locating in an innovation ecosystem with potential disruptors is one strategy for remaining nimble and ultimately fending off disruption. Even traditional companies are following suit in a race to deliver superior working environments. In 2019, we expect to see more companies electing to upgrade their facilities and geographic footprint in order to accommodate the next generation of talent and build strategic partnerships.⁵

Notes

¹ Source: McKinsey Global Institute, “The promise and challenge of the age of artificial intelligence”, James Manyika and Jacques Bughin, October 2018

² Source: Forbes, “How Much Data Do We Create Every Day? The Mind‐Blowing Stats Everyone Should Read” 21 May 2018

³ Source: The Verge, “What is edge computing,” Paul Miller, 7 May 2018

⁴ Source: Gartner, “Forecast: Blockchain business value worldwide, 2017‐2030,” 2 May 2 2017

⁵ Source: Bloomberg L.P., “Morgan Stanley redesigns offices for a “dynamic, millennial” workforce,” Sonali Basak, 8 Oct. 2018

Investment risks

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This article is for Professional Clients & Qualified Investors only. Data as at 30 November 2018, unless otherwise stated. By accepting this document, you consent to communicate with us in English, unless you inform us otherwise.

Where individuals or the business have expressed opinions, they are based on current market conditions, they may differ from those of other investment professionals and are subject to change without notice.

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