Essential Considerations
AI will be the most significant transition in our lifetime- both in terms of size and pace of impact. Companies of all sizes, and in most industries, are currently exploring how to drive productivity through AI-driven solutions. Many worry about being left behind by more aggressive competitors or becoming disrupted by AI-native newcomers.
Investors in private markets need to assess and try to quantify the actual implications of AI for their investment strategies. This blog post will provide guidance related to three of the most essential questions to ask yourself when you establish an investment strategy for the long-term value creation through an AI lens.
AI will transform the business landscape, including the asset management landscape as we know it.
AI in Asset Management
Financial Services companies have historically been early adopters of technology-driven transformation, supported by the industry’s relative technology maturity and the digital nature of the financial services business model. It is hence not a surprise that many Financial Services companies are frontrunners in exploring AI opportunities.
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Innovative Asset Management companies are already experimenting with AI to generate alpha, drive superior operational performance, personalize investment products and manage risks. A crucial differentiator is access to data.
Here public markets differ materially from private markets with its more disperse flow of data. Over time, generating alpha in public markets will be even more difficult since a single analyst will find it hard to compete with a well-trained AI engine. The trend with passive investment strategies and quant driven funds is likely to continue in the public market domain.
- Mega Asset Managers
The largest asset managers have come the furthest, building on their natural “techfirst” mentality. Blackrock is the world’s largest asset manager handling $21trillion of assets, more than the entire US GDP of $20 trillion. Blackrock’s Aladdin platform has been trained on massive amounts of financial data since inception in 1988 and they are now planning to take AI leverage to the next level with a center for AI research called the “BlackRock Lab for Artificial Intelligence”. Blackrock’s mega scale asset management competitors, like StateStreet Alpha and Vanguard, are also exploring ways to stay competitive as they target to catch up with Blackrock/ Aladdin’s headstart with the help of AI and analytics.
- Mid-sized Asset Managers
Most mid-sized players realize that they need to be early adopters of AI to stay relevant. Hedge funds, like Man Group, are early movers in using alternative data for AI-enabled alpha generation. Lion Global Investors has developed specific AI models trained on relevant financial data for the customer segments they target. To stay competitive most mid-sized asset managers will aim to access specific, ideally proprietary, data sets targeting niche segments or selected geographies where they can compete with the largest companies through specialization.
- Family Offices/ HNWI
Smaller investors, Family Offices and HNW individuals, will struggle with bandwidth, insufficiently deep pockets, lack of data, and limited access to specialized talent to address the AI opportunity ona standalone basis. They will instead work in tight collaboration with AI-enabled Private Market Platforms, like ROYC, to access insights for their Private Market investments.
To address the needs of institutions aiming at servicing private market investors, ROYC has developed an easy-to-use and private markets-optimized platform where we maximize the power of embedded AI. ROYC’s platform is continuously updated with value-added functionality,including streamlined investment process, automated capital calls, custom onboarding, and flexible client set-ups. We have created a detailed roadmap for embedding AI functionality in the platform.
We are exploring fine tuned LLMs (Large Language Models) for broad application of AI to optimize core flows in the platform. This will automate historically tedious efforts in filling out information and enable rapid generation of overviews based on aggregate data from multiple sources. ROYC will also use AI for specific high value features,like WealthBuilder.
ROYC will continue to stay leading-edge in adopting relevant AI embedded in our platform so financial investors can take advantage of the AI boom in private markets
Crucial AI questions to qualify Private Market investments
Adopting the latest AI technology alone will not be enough for investors to succeed. Investors targeting private markets will also need to develop a new framework to properly assess the ability of potential investments to adopt to the upcoming AI landscape and the implications on long-term value creation.
As Private Market investors evaluate potential investments from an AI lens, there are three key questions to ask your target companies:
- Do you have a CAIO with the right qualifications?
- Do you have an AI Strategy to stay competitive?
- Is your AI ambition “stretched but realistic”?
If the answer is satisfactory to all three questions, the company is worthy of pursuing deeper due diligence. If the answer to any of these questions is “no” or “fuzzy”, it should be considered a serious red flag and corrective action will be required to warrant continued interest.
Question 1: Do you have a CAIO with the right qualifications?
Most companies have started to experiment with AI, but few are currently coordinating their AI efforts in a structured way. When a prospective investor probes a company’s approach to currentAI efforts, common answers are, in essence: “Don’t worry- we have recruited a team of high caliber data scientists. They sit in a corner over there working on a highly complex task. They have promised to have an answer in a few weeks”.
Very few companies have thus far truly embedded their AI efforts as an integrated part of their ongoing operations and strategic decision making. Leading edge companies will however, in the near term, change this approach and adopt a strategy for how to truly embed AI as a tool for ongoing operations and will have a plan for how to get there.
The most innovative companies realize that the only way to succeed with transformational AI impact will be to assign a senior executive with the dedicated responsibility to coordinate all major AI initiatives across the company. Forward leaning companies, like Morgan Stanley and SAP, are currently recruiting a CAIO (Chief AI Officer) as the newest member of their C-suite leadership team.
The CAIO is not primarily a technology executive. The CAIO is a business executive but who, in addition, has a passion for AI and who has personally spent time building a deep understanding of the foundational AI technology.
Executive Search firms predict that the CAIO will soon be the most sought-after competence in the modern C-suite, especially as the right caliber talent is so rare to find. It is not unlikely that the CAIO will be the future CEO in the next 3-5 years as “deep and relevant” AI skills become a crucial competitive differentiator.
Question 2: Do you have an AI strategy to stay competitive?
Most private market companies have only begun their AI journey and they do not yet have a carefully defined AI strategy. That is OK, as long as they have the intention to turn their current exploration into a targeted AI strategy in the near term. Their ultimate AI strategy will have a perspective on four crucial AI dimensions:
- Personal AI: how will our company equip and train our employees to use AI tools to improve their personal productivity?
- Functional AI: which are the functions in our company that would benefit the most from AI tools (early adopter hints: Marketing; Customer Service; Sales; and Supply Chain)?
- AI Products/Services: how will our company embed AI in the products or services that we sell to our customers, and with what timing?
- Ecosystem AI: how will our company use AI to optimize the end-to-end value chain and improve collaboration with our suppliers and customers?
Most companies should start with Personal AI and Functional AI to experiment, learn and to reach a level of acceptance and understanding among employees in their organization. When the time is right, move on to AI Products/ Services and lastly to Ecosystem AI.
For most private market companies, the transition to an AI-powered company will be a 3-5 year journey. In some cases it will be more urgent given the competitive dynamic and in others they will have a bit more time.
Question 3: Is your AI ambition“stretched but realistic”?
When rapid technology-driven disruption happens, it is very common to be overambitious and try to do too much, too quickly. This approach will fail. Instead, the key to success will be focus. As a potential investor in a private market company, you want to see a vision for the long term AI differentiation but, even more importantly, that long term ambition has to be converted to a tangible action plan with clear 6-month deliverables.
Companies will need to build an agile approach that enables them to adapt to the constant evolution of the underlying technology. Unless they have built for flexibility,they run the risk of investing in technology that could be obsolete in 6-12 months.
Given the rapid pace of the AI technology development a natural reaction could be to “wait and see”. A strategy to be a “fast follower” with the aim to embrace new technology after early adopter competitors have tried and failed could be tempting. This was arguably the right strategy in prior technology transitions (Internet, Mobile,Ecommerce).
The problem with applying a “wait and see” approach with AI, is that the extreme pace of development creates a significant difference between those who have it and those who don’t. If a company’s competitor is ahead in testing alternative approaches to AI, they will at some point in time hit an inflection point where not only the AI technology is mature enough but even more importantly their organization has, through constant “trial and error”, reached a level of maturity in adopting AI.
If that happens at a competitor, it will be close to impossible for your company to catch up. AI is a high-stake game with a likely shakeup per sub industry resulting in orders of magnitude more productive winners and left-behind losers.
ROYC is here to help on your journey to success in private market investments as the AI transformation builds momentum.By consistently answering these three essential AI questions when assessing private market opportunities, you will make the right choices. Let’s go execute!
Author: Jörgen Ericsson, ROYC Senior Advisor
