When Isaac Newton first saw the apple fall from the tree, he was self-isolating on his estate in Lincolnshire to avoid the plague that was ravishing London in 1665. That moment inspired his theory of gravity, of course, which went on to transform our understanding of science.
Although the apple’s fall was coincidentally timed, it is true that countless inventions and innovations have been born out of crises in human history. During the covid-19 pandemic, aside from triggering mammoth leaps forward in vaccinology, living with the virus incepted a culture of problem-solving and innovation. Autonomous food-delivery robots, health-tracking apps – such inventions may not change the world to the same extent that Newton did, but they are by-products of the enforced social and economic changes of recent times.
These evolving priorities have placed greater emphasis on health and hygiene, mobility, inequality, remote working and education and, of course, digital technology. Infrastructure already faced a significant supply and demand gap pre-covid. Throw into the mix the not-so-little problem of global warming, and conditions are ripe for technological disruption to change how we build and interact with infrastructure for generations to come.
Proportion of respondents to Private Funds CFO’s 2022 Insights Survey that are either evaluating or have already implemented AI in their processes
Proportion of respondents to a 2022 survey by Deloitte that said cybersecurity technologies will have the largest impact on infra plans in the next three years of any technology
“Barring the broader macroeconomic environment, there’s undoubtedly an acceleration with regards to anything that brings more digitalisation to what private markets institutions are doing,” says Kanav Kalia, chief sales and marketing officer at private markets technology solutions provider Oxane Partners. “There’s a genuine push for all projects that bring in more technology to make processes more efficient, more transparent and cleaner.”
One of the biggest disruptive forces in action is the advent of artificial intelligence and machine learning and their wide-reaching applications in the infrastructure industry. These range from improving data collection and automating asset management processes, to allowing for predictive data analytics in support of performance and ESG goals.
“In some areas the influence is a lot more than in others, but it wouldn’t be wrong to say that the impact of technology is touching every corner of private markets now, and there are hardly any sectors that won’t be impacted. Although gradual, this is what we are observing with artificial intelligence and machine learning as well,” says Kalia.
Automating processes with AI
AI and machine learning have the potential to transform fund operations, and take asset management from a ‘reactive’ to a ‘proactive’ practice
In affiliate title Private Funds CFO’s 2022 Insights Survey, over a quarter of fund manager respondents said they were either evaluating or had already implemented artificial intelligence in their processes. Although this leaves a large majority of private market firms that have yet to even consider AI or machine learning, the potential for the automated analysis of huge volumes of data to enhance efficiencies is becoming clearer.
“When it comes to the application of AI and ML within the middle office and back office, we can break down into sub-functions including risk management, legal and compliance, performance measurement and attribution, asset management and client reporting,” says Oxane Partners’ Kanav Kalia.
“In risk management, for example, with large infrastructure projects in particular, it can be challenging for operational risk teams managing these project finance deals to keep on top of monitoring the projects from a risk perspective. This is where this technology can really help by screening for risk through capturing data points at the source. The information is captured and fed into an AI or ML engine which helps asset managers to screen for operational risk.”
“It will be a slow burner, but it’s not something that asset managers can ignore for much longer”
Use cases at the asset level, however, are where Kalia sees the most potential for AI and ML to add long-term value – and value in more than one sense. “With a large asset, like a bridge or a toll road, the advancement of 5G, the Internet of Things and smart sensors means we can really capture how the asset is performing on a real-time basis,” he says.
“By overlaying this data with predictive analytics, we can anticipate and detect performance failures and improve performance, sustainability and energy efficiency. This represents a move from reactive to proactive – or even preventative – asset management.”
There are several barriers to adoption when it comes to applying AI and ML technologies, however. Firms need the right technical capabilities, they need to process enough data so that the system can learn from it, and they should be able to scale up the application. Aside from the significant amount of time, effort and cost involved, “there is also inertia to change that firms need to overcome”, says Kalia.
Such obstacles mean that embracing this kind of tech-driven disruption is naturally more feasible for larger infrastructure managers. “It will be a slow burner, but it’s not something that asset managers can ignore for much longer,” says Kalia. “As some of the larger institutions lead on this and see success, it will slowly move the industry forward.”
As fund managers look to build the next generation of infrastructure – with assets that are sustainable, resilient and adaptive – the next generation of technology is stepping up to facilitate the transition.
Using blockchain in reporting
Capturing real-time emissions data is one example of blockchain’s potential
For some time now, ‘blockchain’ has been a buzzword for technological disruption, heralding a wave of change that businesses would be powerless to stop. In reality, progress has so far been slow, but its potential is clear.
“Based on discussions with our institutional clients, we see the potential for blockchain in large infrastructure projects to aid traceability and improve participation,” says Oxane Partners’ Kanav Kalia. “As for when this potential will be fully realised, we cannot say. Some institutions have done preliminary work here, for example issuing bonds within a tokenized framework.”
Darren Wolfberg, co-founder and CEO of digital finance platform Blockchain Triangle, told Infrastructure Investor recently that blockchain has considerable potential to improve climate reporting for infrastructure assets. The technology can tokenise assets to create “a market data-like ecosystem where one company can publish their data to other permissioned stakeholders”.
This could be particularly valuable in the practice of disclosing carbon emissions. “In climate compliance reporting, there are triangulations of reporting between the company (Scope 1 and 2), its supply-chain partners (Scope 3), and the third compliance stakeholder (the regulator, bank, insurance company, asset manager or credit rating agency),” said Wolfberg. “These three parties create a triangulation of data flow that can only efficiently be delivered with market data feeds and blockchain.”
Although progress is slower than expected, according to findings from Intertrust Group, blockchain and distributed ledger technology is the primary focus for the majority of private funds over the next five years – over and above data analytics, machine learning and, indeed, any other type of technology.
Operators prepare to close digital ranks as the era of ‘smart’ infrastructure beckons
In a 2022 survey of public and private sector infrastructure executives by Deloitte, cybersecurity technologies were predicted by 49 percent of respondents to have the largest impact on infrastructure plans in the next three years, behind only AI/machine learning and cloud computing among technology types.
With the next generation of infrastructure set to build on the advancement in IoT technologies to become an interconnected network of ‘smart’ power grids and transport systems, this is beginning to drive a greater emphasis on cybersecurity among infrastructure operators. Even where cybersecurity is already managed, introducing new technologies like AI could alter what digital hygiene looks like.
“We look at cybersecurity from two main angles: risk of operational outage and cost of data breach. AI deployment will have implications for both,” Petter Weiderholm, EQT’s global head of IT strategy, told Infrastructure Investor in July. “The trick is to ‘skate to where the puck is going to be’, which means you will need to protect ever more data and build resilience in more automated systems and processes to be able to detect, respond and recover from incidents. AI already plays a role on the defensive side here.”
The incoming smart era aside, the shutdown of the Colonial Pipeline in 2021 is an ill-famed example of what can go wrong if infrastructure asset owners are not prepared for cyberattacks. Deloitte’s analysis, however, found that an average of 30 percent of respondents globally felt that their infrastructure is not adequately protected from cyberattacks. This was felt more acutely among respondents in emerging markets than developed economies.