Innovation in infrastructure rarely stands still for long. Take aviation, which in less than a century evolved from timber-framed flying machines to the Soviet Union’s An-225 Mriya, a record-setting colossus with a maximum takeoff weight of 640 tonnes and whose cargo hold alone surpassed the entire length of the Wright brothers’ historic maiden flight.
Today, engineering excellence remains at the forefront of infrastructure, but the boom in data has made bits and bytes the new hard currency. Across the asset class, vast artery-like streams of data are being generated daily, motivating operators to adopt a dizzying array of new technologies, and with a wide range of applications.
Against this avalanche of data, artificial intelligence and machine learning are proving their worth as important resources in the digital toolkit of many operators. From building digital twins that mirror physical assets, to deploying AI that can detect operational failures, the technology has the potential to transform legacy working practices across the infrastructure industry.
“Data often comes on screen and then is never looked at again, falling into a black box,” explains Eric Bindler, research director of digital water at Bluefield Research, a US-based advisory firm focused on water infrastructure. “AI can be really helpful in looking back through these historical data sets, interpreting patterns and then finding insights that maybe one individual department or individual operator would not be able to come up with or process on their own.”
Of course, operators cannot rely on miracles. Generating data for data’s sake is unlikely to result in success without a proper strategy put in place. “The escalating volume of data does not necessarily increase opportunities, what counts most is the right quality data,” cautions Joe Perino, principal analyst at LNS Research, an advisory firm focused on industrial transformation. It’s a point reiterated by others.
“You cannot just add sensors and ‘apply AI’ – typically, you want to combine it with data from other systems, and if you run a lot of manual processes, that can be a challenge,” adds Petter Weiderholm, EQT’s global head of IT strategy. “The key questions to answer here are not just about volume, but also what and where are you storing and performing your computing, how are you training your algorithms, what are you trying to accomplish, what processes will that impact, and how do you think about iterating to reach business outcomes?”
Cybersecurity is another key issue at the heart of adopting third-party digital technologies and welcoming greater automation. Hybrid work and the war in Ukraine has increased the risk profile for infrastructure firms, as showcased by the Cybersecurity and Infrastructure Security Agency in the US releasing a series of recommendations this year to mitigate potential cyberattacks.
“We look at cybersecurity from two main angles: risk of operational outage and cost of data breach. AI deployment will have implications for both,” explains Weiderholm. “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.”
In the realm of digital infrastructure, cybersecurity concerns are one of several factors exposing the need for technological advances. “Paradoxically, fibre-to-the-home is extremely fast and efficient from a telecoms perspective, but it is still quite slow and old-fashioned from an IT perspective,” explains Augustin Schneider-Maunoury, asset management director at InfraVia Capital Partners.
The firm’s portfolio company, IFT, is developing a new IT system to support the roll-out of FTTH across France, addressing its fragmented nature and the manual processes involved by providing a platform to connect retail operators quickly and securely to FTTH lines.
“Next to the FTTH network roll-out that we all see happening on the ground, there is an unseen challenge to build a new IT architecture more aligned with the efficiency standards of fibre,” adds Schneider-Maunoury.
A store of value
Industrial innovation is also a key focal point for the energy transition. Modern technologies are helping to drive down the cost of renewable energy, making the sector more competitive and, importantly, attractive to long-term private investors.
As renewable energy grows in the global mix, the intersection between storage and technology will similarly play a decisive role, especially if the goals of the Paris Agreement are to be achieved. “Our entire business thesis is built around the idea that storage is critical to the clean energy transformation,” says Rebecca Boll, chief product officer at Fluence, a US-based provider of energy storage services. “Wind and solar are intermittent assets. They do not necessarily create energy when that energy is needed, and so it has to be stored somewhere and then released into the grid when required.”
Beyond just a store of low-carbon energy, as intermittent renewables capacity grows, storage will ensure well-functioning power networks and prevent grid inertia. “Storage is certainly important for grid stability because whilst renewable generation can be forecast, it cannot be scheduled,” explains Gianmarco Pizza, global head of digital asset management at Fluence.
Adoption of AI will also no doubt help accelerate the energy transition. In the transportation sector, which accounts for around a quarter of global emissions, the shift to electric vehicles will see numerous potential applications for AI, from autonomous decision-making vehicles to predictive battery charging.
At the same time, the inextricable rise of renewables and inevitable pressures on grid stability will increase demand for technologies like AI. Being able to draw from wind and solar data to accurately predict future capacity levels will help ensure consistent baseload generation and prevent blackouts.
“Automated systems, including artificial intelligence, will enable investors to manage assets more efficiently,” says Shami Nissan, Actis partner and head of sustainability. “When it comes to assets like data centres, intelligent systems and machine learning are vital for tracking and adjusting aspects such as server room temperature – heating and cooling, lighting and humidity – making continual micro adjustments to optimise efficiency.”
Maintenance is another important application for operators across the asset class, including renewables providers, extending the life expectancy of assets and preventing operational failures. “On our renewable energy assets, we are looking at predictive maintenance by examining historical trends to see if there are any material deviations,” says Pauline Thomson, director at France-based investment firm Ardian.
Generating clean molecules
Many asset managers are also bullish about the potential for hydrogen to eventually replace more carbon-intensive energy sources. In its 2021 Hydrogen report, the International Energy Agency estimated that global hydrogen demand will rise from around 90 million tonnes in 2020 to 105 million tonnes by 2030 if all plans announced by governments and industry bodies are realised. That figure would have to rise to more than 200 million tonnes by 2030 to meet the conditions of the IEA’s Net Zero Emissions by 2050 Scenario.
Macquarie Asset Management has designs on blue hydrogen, a grade produced from natural gas and its CO2 sequestered through carbon capture and storage technology. In early June, the asset manager pledged its support to South Korea’s plan to source a third of its energy from hydrogen by 2050. Last year, the Asian nation spent almost $702 million on hydrogen projects, with a further $2.3 billion committed to establishing a public-private hydrogen-powered fuel cell electric vehicle market by the end of 2022.
Ardian has already co-launched a dedicated hydrogen fund, which is targeting €1.5 billion. In February, the manager invested in Hy2gen, a Germany-based company that develops, finances, builds and operates green hydrogen facilities.
Advocates for hydrogen technology argue that molecules produced via electrolysis could be used as a clean feedstock to decarbonise the power, transport and industrial sectors. But even if we discount the economics of delivering the hydrogen economy, the reality is that an unprecedented mountain of raw materials will be needed to achieve the energy transition regardless – not to mention the likely impact on the traditional geopolitical world order.
“Technologies required as part of the whole economy transition – be it batteries, smart meters, EV chargers or electrolysers required for green hydrogen – need to be manufactured in much greater quantities,” highlights Nissan. “To achieve this, we will need to significantly increase global availability of raw materials including metals and minerals.”