Ashurst 2023 tech predictions

The effort to achieve net zero demands bold and immediate action to push tech innovations that will create less waste and use less energy at a global level. Expect investment and innovation across the board – from clean energy generation, transmission and storage, to lower-carbon energy solutions such as hydrogen and carbon capture usage and storage, to broader energy saving and efficiency initiatives.

As climate and clean energy technologies mature, we'll see philanthropic partnerships and innovative funding models accelerate the transition away from fossil fuels and seek to help those sectors in which it is difficult to reduce carbon footprint.

Advances in artificial intelligence and ESG data will allow businesses to effectively identify, re-design and build tech-driven climate solutions

There is increasing awareness of the climate cost of processing intensive technology. We will likely see further consolidation of cloud AI processing in larger, more energy efficient hyperscale data centres, and more efficient AI processing hardware being developed.

A maturing climate tech landscape is driving targeted regulatory interventions. With increasing regulatory focus on "greenwashing" and the push for net zero emissions, organisations are investing in better ESG monitoring and data, most obviously in understanding carbon emissions.

Governments are under pressure to manage a "just transition" (a concept that emerged from the 2015 Paris Agreement) that has meaningful climate impacts but leaves no one behind.

ESG factors are increasingly becoming the difference between success and failure for a broad range of consumer and technology initiatives, particularly in areas of heightened public sensitivity like AI and automation.

Leading businesses see ESG goals as core to decision-making – using technological advances (such as AI and algorithmic data analysis) to improve that decision-making is therefore a clear and logical next step. Simply donating to charities is no longer sufficient.

Governments and industry have recognised a chronic talent shortage that can put cyber security efforts at risk and hold back much needed innovation.While businesses compete for talent in a talent pool not big enough to sustain demand, they are also looking at the workforce of tomorrow by retraining talented staff and investing in artificial intelligence and automation technologies to make staff more effective.

Burn-out and psychological safety is a particular challenge in cyber security. How an organisation manages these challenges can create either a death spiral or a virtuous circle – less safe workspaces will lose people, putting more pressure on those who remain – and making recruitment, retention and training or re-training even harder. Organisations able to build a safe and sustainable way of working will find it easier to attract, retrain and train staff.

The tight market for tech talent is leading to a renewed focus on strategic sourcing, including direct investment or acquisitions in supply chains. Successful businesses are not only investing in tech solutions to address current needs, but making longer term investments in the people, culture, supply chains and capabilities required to maintain tech leadership and roll out future waves of innovation.

There has been a stark shift in focus from pure "cyber security" to a cyber resilience, recovery and harm minimisation mindset.

Tech innovation has traditionally focused on operational efficiency and optimising processes. The pandemic, accelerating cyber threats and supply chain disruptions have sharpened focus on security and resilience, particularly in digital and physical supply chains.

Governments are legislating to boost security and resilience in critical infrastructure. As more sophisticated organisations harden their security posture, opportunistic threat actors will focus on weaker links. Organisations are looking closely at not only their own security posture, but that of their suppliers, customers and intermediaries.

We are seeing a shift from a point-in-time security assessment as part of initial procurement to ongoing auditing, testing and improvement of security and resilience systems across a supply chain. Suppliers need to be able to demonstrate resilience and security credentials to sell into most industries.

Investment in security systems and technology is essential – such as systems to rapidly identify and patch vulnerabilities, recognising that in a complex IT environment it can be difficult to know what software and software components are in use. Vendor-managed cloud-hosted systems and software bills of materials (SBOM) that keep track of software components are becoming attractive options.

Cybersecurity as a Service offering and privacy enhancing technologies appear to be an attractive tech-driven solution, particularly in a tight market for cybersecurity talent. But businesses are also adopting a longer term strategy of building organisational capability (for example, by focusing on training and development rather than competing for experienced cyber talent).

Information technology and operational technology systems are blending as physical equipment becomes connected and aware, for example "smart cities" and automated manufacturing – creating new points of attacks, and increasing the risk that an attack may impact the physical safety of people.

Every technology decision will need to take into account resilience and security implications, and consider how decisions impact an organisation's exposure to threats. In some cases this may significantly increase the cost of bringing nascent technologies to market and stifle early growth, but will ultimately lead to a healthier tech ecosystem.

Driven by our online experiences, consumers and businesses now expect services to be tailored and informed by our personal circumstances. We expect recommendations to be personalised, and we expect algorithms to be informed and intelligent.

But with the ongoing threat of cyber-attacks, organisations are asking hard questions about what data they collect and retain, why and for how long.

Being the victim of a cyber-attack is not a breach of privacy laws in and of itself. But regulators have a duty to ensure that organisations that are not compliant with relevant privacy laws are subject to appropriate penalties. If an organisation hit by a cyber-attack has (for example) over-collected or over-retained data, expect regulatory action.

Governments and businesses are investing in technologies to reduce the need to collect data and to reduce the risk of harm following a data breach – for example, by implementing digital IDs instead of collecting and storing sensitive data such as government identifiers. As digital IDs become more reliable and pervasive, the value of stolen identifiers to hackers may also decrease.

Governments across the world are making hard decisions about how to prioritise data security and privacy rights against the opportunities of personalisation and data insights, risking a global splintering of regulatory approaches.

AI is hitting the mainstream – more "off the shelf" solutions are available, including low-code or no-code options, allowing AI to be applied across the business without needing an army of programmers. This is convenient given the shortage of AI talent. Tools like "no-code" AI, dedicated hardware and cloud solutions, and pre-trained AI models allow AI to be more easily deployed and redeployed at scale.

The prospect of "easy AI" introduces its own challenges around data and privacy governance and compliance, and ensuring responsible and ethical use of AI. A key challenge will be to avoid bias in AI systems or data sets that may lead to discrimination and lower quality decision making. The current trend towards stronger privacy laws and enforcement might counter-intuitively reduce the quality of data available to train and monitor AI systems, and reduce an organisation's ability to identify and fight bias.

Moves to regulate AI directly have focussed on high-risk use cases, and we expect this trend to continue. The European Union will push ahead with regulation of certain AI, with its AI Act expected to be finalised in 2023. We expect a risk-based, and meta-regulatory approach in most sectors – an approach that places the onus on an organisation implementing AI to understand and manage risks, and to be able to demonstrate this to a regulator.

We will see more sector-based regulation of AI through existing regulators. For example, AI in banking and finance will be under significant scrutiny as part of the overall regulatory agenda of managing operational risks in the sector.

We are also seeing a push for more transparency, challenging the traditional secrecy of tech innovators – particularly for "building block" AI widely used in other applications such as 2022's explosion of generative AI such as ChatGPT, Stable Diffusion and DALL-E.

A controversial battleground is the intersection of artificial intelligence and data privacy. Governments across the world are modernising privacy laws for the digital age, balancing the societal and economic benefits of wider uptake and development of artificial intelligence against data privacy concerns.

Some jurisdictions, like the UK, are actively courting a "pro-innovation" agenda that may provide a competitive advantage through less red tape. Others, like the European Union General Data Protection Regulation (GDPR), are backing more robust "pro-privacy" protections driving consumer confidence.

Differing data privacy rules, and associated business risk profiles, will influence how we invest and how we innovate today, and what technologies will be mainstream tomorrow.

Advances in artificial intelligence bring new opportunities to automate, including for knowledge workers. We've seen a range of success stories as well as teething problems as businesses look to increase quality of outcomes and reduce operating costs.

Automation has been an area of focused investment in some sectors for decades, but with the combination of connected or Internet of Things (IoT) devices, artificial intelligence and digitalisation, we are seeing more effective and predictive automation – for example, using a "digital twin" of an automated facility to plan for and test the impact of hypothetical disruptions, or of a mobile tower to optimise radio frequency utilisation and equipment maintenance.

Driven by COVID-19, the health tech sector is seeing particular growth in digitalised services, IoT and medical robots, and the use of artificial intelligence for medical research – laying the groundwork for more advanced analytics and automation in health care in the future.

Industrial automation and digitalisation will continue to spread from mature innovators to the rest of the economy. Mature players will refine their digitalised models to reach further into supply chains to become more responsive, proactive and (most importantly) predictive. We expect greater use of digital twins and artificial intelligence to turn systems developed for operational efficiencies into strategic tools to digitally test innovations or resilience.

While businesses will likely want to automate more with an expected economic downturn, they will need to contend with a shortage of experienced tech workers, extending beyond internal workforces to the workforces of key suppliers necessary to deliver projects. At the same time, an economic slowdown may bring more unemployment, particularly for entry-level workers. The jobs that may be simplest to automate may be the ones that are easiest to staff with humans. In this environment, we will see a focus on automated or technology-assisted knowledge or technology work (such as no-code or low-code software) and AI-driven assistance tools to assist knowledge workers (such as GitHub's Copilot).

Advancements in industrial IoT will be held back by security concerns and a lack of security and communication standards. We are seeing a steady but slow alignment of standards and better mutual recognition frameworks – but we are not yet at the stage where industrial IoT can be safely considered an "off the shelf" option.

2023 will see continuing and increasing investment in quantum capabilities, including post-quantum encryption and new hardware solutions.

The race to quantum is only partly about the benefits the technology will deliver – investment in quantum has been prioritised by governments because developed quantum computing solutions will be capable of being used to compromise traditional encryption methodologies. That being the case, nations that fall behind in the race to quantum risk losing primary defences against cybercrime and cyberwarfare.

Processing-intensive applications like artificial intelligence will be transformed by quantum capabilities – 2023 may see the beginnings of new, more powerful and more climate-friendly processing.

In the near term, we expect more immersive experiences to be on offer, but the promise of a ubiquitous metaverse will take more time.

Many of the "component parts" that may make up an interoperable and ubiquitous metaverse are mature technologies with current consumer and business use cases – virtual and augmented reality, digital assets, decentralised technology and low latency internet are all mature. While some businesses have invested heavily in metaverse technologies, remote and hybrid work is still largely done by email and video call.

Will 2023 be the year for virtual remote work to go mainstream? We think it is more likely that 2023 will see growth in the use of metaverse technologies for narrow use cases – such as augmented and virtual reality education and training.

But of course, gaming and entertainment will lead the way.

2023 will see the continuation in the trend of investments in and deployment of all forms of digital infrastructure (although the availability of debt financing may impact upon some tower and fibre deals). However, two trends to watch out for this year include the deployment of 5G standalone networks and the adoption of private networks.

There will be ongoing investment by operators in 5G deployments despite the challenging business case. There has been much hype surrounding 5G over the years but it has so far failed to live up to its potential or to find the “killer use case”. However, a migration to standalone networks with 5G radios running on top of a 5G core network is necessary to provide the transformative potential of 5G. In 2023, we will start to see the second wave of 5G deployments as telecoms operators deploy 5G standalone networks. Standalone networks, based on a cloud virtualised 5G core, will bring faster, more reliable and secure connectivity creating the foundation for advanced enterprise applications.

The adoption of new private networks has, to date, been slower than anticipated. Due to the high cost and complexity of planning, deploying and managing private networks take-up has been mainly limited to larger organisations. In 2023, we expect to see more operators building partnerships (such as that between BT and Ericsson in the UK) to offer simpler private networking solutions to increase wider adoption.

As with all industries the impact of inflationary pressure and rising energy costs will be a challenge for operators in 2023. Driving operational efficiencies (including for example, automation, digital twins etc) and reducing power consumption will be a priority for many. In more mature markets, telecoms operators may also start to consider decommissioning legacy networks earlier than planned.