Looking ahead is always a difficult task. While the new year provides a chance to rethink your strategy and decide where to direct your efforts, it may be difficult to separate true trends from hype. This is especially true in the field of technology. Consider the hype around NFTs, cryptocurrency, and the metaverse this time last year. By the fall of 2022, NFT markets had fallen 90%, we’d entered a harsh crypto winter, and a thriving metaverse remained a pipe dream. Distinguishing genuine innovation from hype might be the difference between a major triumph and an expensive flop.
2023 will likely be a more sober year in tech. Geopolitical and economic uncertainties are injecting more caution into the next phase of tech’s evolution. Leaders will have to search for ways to do more with less, find value where innovations overlap, and strategically invest in technologies that are hitting a tipping point.
Look out for combinatorial trends.
In 2022, we can identify 14 technology trends that have the potential to change how we work and live. These included space technologies, clean tech, AI, and immersive reality technologies. For executives in 2023, the challenge will be not just betting on individual trends or ramping up software engineering talent, but thinking about how all these technologies can create new possibilities when they’re used together — what we call combinatorial trends.
In many domains from consumer to enterprise across all sectors, combinatorial trends are creating exciting new possibilities. Because of the vast array of possible combinations possible, creativity in “mixing the ingredients” becomes a key to success. Consider the technologies in a new electric car: cloud and edge computing that power the networks connecting cars, applied AI and ML that enable autonomous decision-making and driving logic; clean energy and sustainable consumption technologies that create the core of vehicle electrification through, among others, new lightweight composites and battery capability advancements; next-gen software technologies enable faster development of customer-facing features and reduce time-to-market, while trust architectures ensure secure data sharing. Together, these technologies combine autonomy, connectivity, intelligence, and electrification to enable a new future of terrestrial mobility.
Similarly, new patient-level treatments such as blood type-based treatments or cell-targeting are powered by advances in bioengineering (e.g., novel therapies based on tissue engineering), immersive reality technologies (e.g., remote therapies), web3 (e.g., traceability, interoperability, and permanence of EHR records), applied AI and ML (e.g., improved image processing, predictive health alerts), and cloud and edge computing (e.g., increased data access and processing capabilities). The impact is not simply additive – it’s multiplicative.
In 2023, we expect to see some of these combinatorial approaches start to scale. That might include the approach that led to mRNA vaccines — a combination of bioengineering technologies such as genomics, applied AI, and the industrialization of machine learning — being applied to other diseases. We also see signs that the combination of advanced mobility, advanced connectivity, and applied AI will be applied to less sexy but economical critical logistics problems as a path to building supply chain flexibility and resilience. When looking at how you plan to invest in technologies over the next year, try to think holistically and consider how they make work together to unlock new opportunities.
Prep the board for tipping-point technologies.
Game-changing technologies, such as 5G, AI, and cloud, are hitting tipping points for mass adoption. Our research shows, for example, that companies are looking to move about 60% of their IT estate to the cloud by 2025. And more than 50% of companies report they’ve adopted AI in at least one function in their business. While boards may be preoccupied with flattening or reducing investment in IT budgets, they need to keep their energies focused on the risks and opportunities in these big shifts.
Doing this requires the board to prioritize the budget for upgrading IT foundations that enable speed, security, resiliency, and reusability. These aren’t the sexiest investments, but automating processes, investing in data foundations, cleaning up tech debt, and continually renewing the IT architecture are needed for the business to have a chance of taking full advantage of the new technologies coming online.
The board is better positioned to advocate for this approach than anyone else. IT’s priorities are too often shaped by individual business units or divisions. The investments in tech foundations – “IT for IT” – benefit the entire business, so require the board, working with top management, to guide and direct the effort. A good rule of thumb is that 15–20% of IT’s change budget needs to be allocated to this foundation work.
Leaders can’t assume the board will come to this vision on its own. For the board to be able to engage at this level, the CIO and CTO will need to have more continual and frequent dialogs with individual members of the board about tech priorities and needs.
Free the engineers you already have.
Layoffs in the tech sector and belt-tightening measures at most enterprises mean that tech leaders in 2023 will need to master the art of doing more with less.
The trap will be to ask your tech people to simply do more. Instead, try getting them to do less — less admin work, less bureaucratic work, and less manual work. In many large organizations, engineers spend as little as 50% of their time on actual development. Imagine improving that by just 10 percentage points for a large company that has thousands of engineers. There are huge amounts of productivity there for the taking.
CIOs can capture it by being more scientific and methodical in developing and applying the craft of engineering. Specifically, there are a few steps they can take:
Be more thoughtful about team makeup and get a handle on who your top performers are. Individual engineer performance can vary 2-3x between teams.
Look into how many distractions you can take off of your engineers’ plates. Even relatively simple fixes, like cutting down on meetings or making the “agile ceremonies” more productive, can free up substantial time.
Lastly, go all out on automation to remove the scourge of manual tasks that weigh down engineers. Automating testing or compliance can have a huge impact in terms of freeing up engineer capacity to do what they love.
This isn’t just a productivity issue; it’s a talent issue. If you want your company to become a destination for top engineers, you need to create a work environment where engineers can do what they love.
Get your head in the cloud.
Last year, many CEOs changed their outlook on cloud computing, essentially going from “I’ll do it because that’s what my CIO recommends” to “I want to be all in.” This point came home to me recently when the CEO of a large bank expressed frustration with the lack of incremental progress on the cloud. Rather than rolling back the program, however, he declared a much more ambitious goal and an accelerated timeline to get there.
Right now, companies have a can’t-miss opportunity to ramp up their cloud ambitions: as tech companies limit head-count and eliminate programs, top talent — not just the bottom 20% performers —are coming on the job market, While many of them are being snapped up quickly, companies should think through how to move quickly when cloud talent becomes available so they can take a big step forward in their cloud capabilities.
The big question, then, is how companies are going to harness these two trends. Most corporate forays into the cloud have been limited to simply moving applications from their own servers (often referred to as “lift and shift”), or building test and development environments to try out new programs. But now is the time to think bigger and smarter.
In 2023 companies should focus on building out strong cloud foundations that allow them to take advantage of the most important benefits that the cloud provides (e.g., scaling applications or automatically adding capacity to meet surges in demand). That means developing the right application patterns (code base that is applied to multiple applications or use cases). It also requires putting in place strong cloud economics capabilities, called FinOps. Recent McKinsey research has shown that companies tend to not really focus on cloud costs until they break $100 million, which is not just a tremendous waste but also a wasted opportunity to generate value. FinOps capabilities can monitor and track spending, determine the unit economics for various cloud usage scenarios, and translate the business’ consumption needs into optimal cloud offerings and pricing arrangements.
The cloud is changing security.
For years, security was treated as a blocker — albeit a critical one — that slowed progress to ensure security protocols were in place. In 2022, however, that started to change profoundly prompted by the big commitments companies made in moving to the cloud. This shift created a useful forcing mechanism for CIOs and CISOs to rethink security’s role, particularly how to improve the business’ risk posture.
That trend will accelerate in the coming year, for a few important reasons.
First, companies are taking the opportunity to automate security as they migrate applications to the cloud. This is because businesses themselves as well as cloud service providers are upping their own security game. Providers have poured billions of dollars, especially into new security tools, for example, to automatically scan code uploaded by developers for cybersecurity issues and reject code with vulnerabilities, providing clear recommendations for what fixes to make when they do. Most security issues are the result of code and system misconfigurations, which means automation will radically reduce the number of security breaches. (At one large bank, for example, breaches dropped 70–80% after implementing security automation.) There’s another benefit, too: this system of automated feedback allows developers to increase the pace of development by as much as 10x and is a much better developer experience.
Second, as more heavily regulated industries like banking and pharma move to the cloud, regulators themselves are rethinking what the pressure points are. They are already becoming more prescriptive about security and compliance standards for the cloud, and thinking about other issues, such as the significant concentration risk. What if one of the big CSPs goes down, and 30 banks with it? While there won’t likely be real answers to these new questions in 2023, we can expect to see the contours of new policy start to emerge.
Decentralized AI is changing the playing field.
Last year brought huge strides in AI “decentralization” — the trend of expanding access to advanced AI technologies that were traditionally available only to players with access to massive, centralized, proprietary data sets. Products such as Stable Diffusion and ChatGPT have enabled a wider set of enterprises as well as individuals to access and interact with deep learning models that otherwise would be restricted to institutions with very large datasets. The implications are enormous, from improving search to increasing developer productivity.
An analysis through QuantumBlack, AI by McKinsey, indicates that in 2023 we can expect to see early signs of how this decentralization can disrupt different sectors, likely starting in the entertainment, gaming, and media areas where traditionally we’ve seen new technologies make early inroads.
The big challenge and opportunity for companies in 2023 will be to take advantage of these decentralized AI capabilities — and what this technology might mean for their business models. For the CIO or CTO, the focus will need to be on how to rework their architectures to easily incorporate application programming interfaces (APIs) (e.g., from OpenAI, Stability.AI) to embed “intelligence” into a wider swath of applications and processes. This capability can, for example, provide automated suggestions of code or code libraries to draw from or auto-generate code to kick-start the development. The goal should be to have AI-driven intelligence built into every part of the technology stack. Enabling this means allocating sufficient resources to experiment — top innovators allocate 1–5% of their revenues to innovation that could yield disproportionate returns. Protecting this budget will be especially important as businesses feel the screws tightening on budgets since the ability to effectively innovate during downturns allows companies to position themselves to grow quickly when the economy recovers.