Transforming traditional infrastructure

It is no secret that much of the infrastructure in developed economies is old and in need of replacement. Across numerous sectors, including transport, energy and utilities, cracking concrete and strained steel is forcing asset owners to consider costly replacements. However, though this may pose expensive conundrums for some, this also represents an interesting opportunity to upgrade these assets through the incorporation of digital technology.

The applications of digital technology in infrastructure have rapidly expanded and are playing a transformative role in these assets’ development. Phoebe Smith, managing director at Patrizia Infrastructure, has seen these changes emerge first hand.

“Digital technology has been a huge catalyst for change in infrastructure,” says Smith. “Sometimes referred to as ‘Infrastructure 4.0’, digital technology will only become more embedded within infrastructure in the future, in the same way that it is other sectors of the economy. Its impact can be seen across a vast range of sectors.”

These applications of digital technology come in several guises, but they arm investors and asset owners alike with information. Given the significant amounts of capital required in the long-term construction of assets, sharper insights can help better inform investment decisions around these projects.

Rajesh Sennik, partner in KPMG UK’s digital infrastructure transformation practice, is seeing multiple instances of technology dictating critical decisions around investment. He says: “It is about utilising data to extend and optimise the lifespan of projects.

“For example, by using sensors to measure various performance metrics of an infrastructure asset, it is possible to undertake predictive maintenance to anticipate and prevent any potential issues that could damage it. As a result, the investment in infrastructure can be optimised for a higher return.”

Such technology isn’t just helpful from the outset but is proving useful during the lifespan of an asset. Maintenance can mean costly expenditure, especially for ageing infrastructure, and digital technology can help investors stay one step ahead of the curve.

At Principal Asset Management, portfolio manager Emily Foshag has increasingly seen the combination of sensors and machine learning algorithms to highlight when infrastructure failures may be due to happen. This is especially the case in electric, gas and water utility investments, where down periods for infrastructure can have significant and immediate impacts on the wider population.

“Maintenance can then be prioritised based on the condition and performance of specific equipment, minimising downtime, extending asset lifespans and maximising returns on capital,” adds Foshag. “Utility management teams are also better equipped to respond in advance of equipment failures, potentially avoiding safety-related disasters that have challenged utility companies in the past, such as gas leaks, electrical fires or water main breaks.”

Giving an example of how this is playing out in her portfolio, Foshag points to recent investments in toll road operators that can adopt dynamic pricing models using digital technology.

“Digital technology supports operators in optimising pricing and therefore profitability by taking into account how real-time changes in traffic can alter a driver’s willingness to pay for congestion-free travel,” she says. “We have also seen digital technology used by toll road operators to enhance safety outcomes on toll roads and to optimise locations for off/on ramps and new lanes.”

The role of AI

In 2023, ChatGPT captured investors’ imaginations and opened endless new opportunities around AI. Infrastructure has been no different, and AI is already being explored in terms of how it can enhance investments and oversight of these assets.

“At a high level, AI is a real game changer,” says Ralf Nowack, a director at Actis and head of operations  for the firm’s Long Life Infrastructure Fund. “It has powerful applications across different sectors of the economy, and it already has a wide array of use cases in infrastructure, from revolutionising preventive maintenance to optimising market transactions.”

AI may be a “game changer” overall for the asset class but this is manifesting in many applications at a localised level, in particular enhancing how data gained through digital technology integrated in infrastructure is used. This means much stronger analysis of data.

Patrizia’s Smith explains the role cameras play in this, using AI to identify and differentiate objects with machine vision learning. The technology normalises the data, which allows it to classify and tag objects. Over time this allows patterns – and more importantly, anomalies – to be identified.

“While how you integrate and immediately benefit from something like AI is more apparent in a subsector like smart streetlighting or EV charging than for other assets, the ability to collate data, understand patterns and then draw on this to manage and optimise the performance of your assets has been transformational,” adds Smith. “To put it very simply, if it moves, you can put a sensor on it and therefore make ‘dumb’ infrastructure smarter.

“This data will improve the delivery of essential services, such as energy systems, the way we engage with citizens, and health services, amongst others.”

There are many examples of how technology is already being incorporated within infrastructure portfolios. At Actis, Nowack is seeing AI being used to help increase the accuracy around renewable energy generation.

Renewable energy poses challenges to traditional energy frameworks due to the inconsistent nature of weather patterns. In India, Athena Renewable Energy is using AI to ensure peak efficiency of energy production and help reduce downtime.

“[Planning around renewable energy deviations] can be extremely challenging, as low-level, transient cloud movements are very difficult to predict accurately using traditional data sources such as satellites,” says Nowack. “At Athena, we are working with the regulator to enhance data inputs and independently developing our algorithms, with partners, to enhance generation prediction.

“We are also collaborating across industry (the Solar Power Developers Association) to leverage collective expertise. This will help minimise penalties to generators while creating a more stable and reliable grid for the consumer.”

With the energy transition increasingly dictating infrastructure decisions, the overhaul of these networks presents a natural opportunity for the integration of digital technology. The demands of a modern, low-carbon and digitally connected society make integration with this technology a natural response, according to John Carey, head of infrastructure debt at Legal & General Investment Management. An added benefit of this technology, Carey says, is the ability to create additional infrastructure investment opportunities with attractive risk profiles.

An example he gives of this is the use of digitalised Supervisory Control and Data Acquisition (SCADA) systems in clean energy. “In the L&G NTR Clean Power (Europe) Fund, asset managers can monitor the real-time performance of our generation assets, with the data streams themselves being processed by Microsoft PowerBI,” he says.

“While, historically, an asset manager would have had to wait for a monthly performance report from a subcontractor, having direct access to this information allows for issues and underperformance to be identified, and – as a result – remedied earlier. This builds portfolio resiliency.”

Weighing up the costs

Infrastructure projects already require high levels of capex, and the introduction of digital technology introduces additional costs for investors. As well as the hardware involved – including sensors, cameras and complete Internet-of-Things networks – these require users who know what they are doing. This kind of expertise is critical, according to KPMG’s Sennik.

“[Digital technology] challenges the status quo and brings innovation to bear. However, that new expertise must work effectively with the existing core business. The leadership and governance model is critical to enabling that.”

Though this may present higher up-front costs, in return asset owners receive better insights which can strengthen the efficiency of infrastructure and deliver tangible savings. Better data allows for the lifespan of an infrastructure asset to be more accurately forecast and potentially minimise capital shortfalls and maintenance costs. LGIM’s Carey is already seeing this feature in discussions between investment teams.

“This has the potential to reduce the physical degradation of assets and reduce maintenance spend over the asset’s lifetime. These improvements enhance the potential returns for investors, and the cost at which we can deliver essential goods and services to our customers.”

Digital technology is arming infrastructure investors with unprecedented insights and, to use Smith’s words, making dumb infrastructure assets smarter. Although higher investment will be needed to make the most of this, this needn’t necessarily mean overhauls of investment processes to make room for these applications.

Infrastructure remains an asset class of long-term holding periods and digital technology can have a positive impact through incremental improvements. Nowack says his team are looking at “low-hanging fruit” in the technology space and taking advantage of the wide variety of opportunities available in this growing market.

“It is worth noting that infrastructure operations rarely need costly bleeding-edge AI developments, as a gain of six to 12 months of competitive advantage has less impact than it would in, say, a trading floor,” says Nowack. “Setting yourself up as a ‘fast follower’ to new ideas that are proven to work is more industry appropriate, and more cost effective. This is particularly relevant given the durations for which we hold our investments.”