Armed with these insights, organizations and their teams will have a greater understanding of the risks, costs, impacts, and likely outcomes associated with their projects. This makes them better placed to absorb, adopt, and leverage AI and other emerging technologies, and convert them into tangible business value. An Enterprise Architecture (EA) and the tooling that supports it can provide these capabilities. However, success hinges on a shift in the perception of EA from being an IT capability, to a critical business discipline.

We hope you will find some valuable insights within these pages to fuel your innovation engine, propel your organization to new heights and gain a stronger ROI from emerging technologies – be that AI, or whatever comes next.

This report examines the current state of emerging technology research and innovation projects within large global enterprises, based on a survey of 700 CIOs and other senior IT leaders in organizations with more than 2,000 employees.

It explores the driving forces behind the continued interest in emerging technologies, such as AI, shining a light on the potentially transformative impacts they can have. The report identifies the key challenges organizations experience as they try to realise these benefits and highlights how they can overcome them by adopting a mature, data-driven execution strategy.

of CIOs say that, if successful, their investments in emerging technologies can put them at the forefront of their market.

Only 53% of emerging technology adoption projects in the past five years have delivered measurable benefits and impact.

of CIOs are worried that competitors will “eat them for lunch” if they don’t move quickly on AI.

of CIOs say it is difficult to maintain full visibility and control of risk across the IT portfolio and anticipate the impact of evolving regulations in emerging technology adoption projects.

of organizations rely on manually mapping – or do not map at all – to determine the impact of a new technology on existing processes and capabilities, and the potential benefits it will deliver.

of CIOs recognise the need to be able to constantly alter course to ensure success with emerging technology adoption projects.

This report identifies that there are three factors CIOs need to master to maximize success: balancing risks and rewards during emerging technology adoption; taking a long term view on their investment decisions; and maturing their enterprise architecture from an IT function to a business discipline. In this report, you will learn more about why these factors matter and what steps your organization can take to drive success on your innovation journey.

As you read this report, it’s worth considering how these findings apply to your organization and what gaps you may have that are preventing you from realising the full value of emerging technologies – here are five questions to start you off:

Key considerations before embarking on emerging technology research

Emerging Promise: AI is Winning the Race for Investment

Almost all CIOs (91%) agree that, if successful, such investments can put them at the forefront of their market.

However, given the experimental nature of emerging technology, it is perhaps unsurprising that the overwhelming majority (99%) of CIOs say the success rate of such projects tends to be lower than that for more established technologies.

An absence of an existing playbook, combined with a lack of skills and knowledge can hamper efforts. As a result, only half (53%) of emerging technology adoption projects in the past five years have delivered measurable benefits and impact.

Companies investing millions in research and innovation, but success can be elusive

As new technologies continue to emerge, organizations will have to carefully consider how they balance upside and risk, failing fast to come out in front and maintain support for future research and innovation projects.

Looking at the areas where emerging technology investment is being focused, AI emerged as a clear winner. CIOs are all too aware that a failure to adopt AI technologies quickly could mean they lose a crucial competitive advantage that is difficult to recover.

CIOs are spreading their investments across multiple types of AI, with GenAI taking the lead, with a wide variety of use cases that they wish to pursue.

CIOs have several goals for such projects, with improving customer experience being the number one driver – while identifying areas for revenue growth and improved access to data and insights also rank highly.

Notably, future-proofing and competitive advantage ranked at the bottom of the list of drivers, suggesting the promise of what the technology can deliver in the shorter-term is of greater consequence to CIOs.

Personalising services and offerings by classifying people based on behaviour, socio-economic status or personal characteristics

Managing access to key services - for example to reduce abuse or fraud

Generating or editing content, such as text, images, audio and video to drive engagement with customers and other stakeholders

The variety of use cases for AI, coupled with the experimental nature of emerging technology research projects, increases the risk of failure if organizations don’t have a clear execution strategy. Many could find themselves simply ‘AI washing’ by developing solutions that add little value to their previous capabilities.

Improved customer experience

Reduced security risk

67% Improved regulatory compliance

66% It’s a cool technology

63% Competitors are adopting it

61% Pressure from leadership / investors

46% Future-proofing

46% Competitive differentiation

Opportunities for revenue growth

Faster time to market

Improved sustainability

Greater efficiency / reduced costs

Improved access to data / insights

Improved workforce safety

Organizations investing in custom-built AI solutions most commonly plan to build in-house with their own technology teams (39%). Another third (33%) of organizations will partner with a services provider or systems integrator to deliver their project, while over a quarter (28%) will work with an AI start-up vendor.

Emerging Tech: No Reward Without Risk

The transformative promise of emerging technologies must be balanced with the potential risks of investing in relatively untested use cases.

While CIOs accept that not every emerging technology project will deliver benefits, they are still under pressure to minimize any risk to business continuity or future innovation.

If they fail to plan for and manage these risks, organizations could find it more difficult to justify future research and innovation projects. The risk extends beyond short-term financial costs. Organizations also need to consider the potential for disruption to their existing operations that leads to damaged reputation, as well as the loss of market confidence that comes from delayed or failed innovation projects.

Flawed impact analysis could lead to flawed decision-making

Many organizations find it incredibly difficult to conduct impact analysis or forecast a return on investment (ROI) for emerging technologies upfront. In fact, 69% of CIOs say predicting the ROI on emerging technology is often a ‘finger in the air’ exercise.

On average, CIOs assess three different types of insights, data, and information to evaluate the likely impact of an emerging technology before they invest in a research and innovation project.

The experimental nature of research projects means that it’s usually impossible to obtain a clear picture of how an emerging technology will impact an organization before investments are made. As such, CIOs need to be prepared to embark with some element of risk and questions still to answer.

74% of CIOs say it sometimes takes so long to gather the input of everyone who should have a say on emerging technology adoption that they’re late out of the starting blocks.

67% of CIOs say by the time they’ve made a call on adopting an emerging technology, it’s often no longer emerging and they have lost the competitive edge.

As CIOs evaluate an emerging technology, it’s critical to ensure any investments support the organization’s business objectives. Time is of the essence, but it’s also important to ensure safe adoption processes - especially when exploring high risk technologies such as AI.

To address this, CIOs need to work hand in hand with business leaders to ensure they are working toward shared goals, with a clear understanding of risk. Strong alignment between IT and business leaders is key to minimizing risk, while maximizing the speed and success of research and innovation projects.

of CIOs say the need to act quickly means they invest in emerging technologies before establishing a business case for the technology.

of CIOs say the rate at which new technologies are emerging makes it difficult to know which horse to back and which is going to fall at the first hurdle.

This report shows that there is no standard approach for forecasting the impact of an emerging technology. More than a third (36%) of organizations manually map where a technology will fit alongside their existing processes and capabilities to identify potential benefits and teams to involve. 29% have a tool or platform that can automate this process for them, and around a quarter (24%) rely on market research or modelling to aid decision-making.

However they evaluate an emerging technology project, it is often difficult to identify the impact it will have on existing processes, leaving organizations exposed to unexpected risks. CIOs urgently need to address this, with a mechanism that enables them to connect the dots between an emerging technology initiative and its impact on the current and future state of the organization.

The continuous need to pivot during emerging technology research projects means that it can often be years before organizations realize any benefits. However, CIOs widely accept this.

Only 32% of organizations look for a tangible ROI from an emerging technology adoption project within the first 12 months. Just over a quarter (26%) of CIOs expect to see an ROI within five to ten years.

To maximize the success of their emerging technology research projects, it’s important that organizations have established teams and processes to support and deliver them.

One-third (33%) of organizations have a dedicated team for managing innovation. The majority (46%) have a cross-functional team, while 21% establish teams and processes as needed.

Most organizations (66%) say IT teams are primarily responsible for innovation management and new technology adoption projects, 19% have an enterprise architect take the lead, and 15% grant product owners the responsibility.

A dedicated executive to sponsor innovation (i.e., Chief Digital Officer)

Dedicated events for teams to pitch innovation ideas to executives

Partnerships with external companies such as disruptor start-ups

Approaches to Managing and Delivering Innovation

Organizations use multiple tools to enable their teams to manage technology research and innovation projects.

Many of these tools weren’t designed with emerging technology projects in mind, making it difficult for teams to access the insight and information they need to make the right decisions at the right time. A project management tool might be well suited to the operational aspect of the project, but will fall short on visualizing the impact of the new technology in the IT estate as a whole.

Cutting projects that aren’t business critical or growth enablers might be the right thing to do, even if the ideas they’re based upon are great. As a result, freeing up time and saving money can empower the organization to onboard new projects faster and leverage emerging technologies and their possibilities before its competitors do.

Organizations therefore need to constantly evaluate the impact of an emerging technology throughout their research projects, so they can improve their understanding of the business case and pivot faster, to drive a higher rate of success.

of CIOs say the speed at which the market, technology, and regulation changes means they have to constantly pivot emerging technology adoption projects as they learn new things.

More than two-thirds (68%) of CIOs say if they didn’t constantly alter course during an emerging technology adoption project, it’s unlikely any of their initiatives would ever succeed.

Research published by The Institute of Engineering and Technology (IET) has reinforced the importance of this, showing that organizations that implement benefits management processes during project execution realize substantially better benefits.

Organizations rely on several key ways to evaluate the benefit of an emerging technology adoption project as it progresses.

These approaches are difficult to operationalize using the collaboration and project management tools that many organizations rely on to support innovation.

A modern EA function is central to using emerging technology research and innovation projects to advance an organization’s overall business strategy. This provides the data, insights, and information that organizations need to fully understand the risks, costs, impacts, and outcomes of adopting an emerging technology, so they can drive stronger value from their investments.

However, just 11% of CIOs say they have a mature enterprise architecture supported by a continuous effort to drive improvement at all levels of the business. A little more promisingly, more than a third (36%) say enterprise architecture is central to the business and informs all technology investments, with regularly updated documents and processes.

Despite this, 33% of CIOs say their enterprise architecture function relies on time-consuming processes that delay innovation and leave them blind to the impact of change.

Modern Enterprise Architecture (EA) is a discipline that enables business execution in a continuous and reliable way. It is a data-driven, dynamic and democratized approach to designing and managing an organization’s people, processes, information and technology to align with business goals and enhance efficiency, agility, transparency and innovation.

Before embarking on an emerging technology research project, it’s crucial that as much as possible, organizations mitigate any unique risks relating to that technology. Each technology and use case carries its own specific risk, so organizations need to identify and factor these risks into their execution strategy. The current focus on investments in AI stands as the perfect case in point.

Many of the most common AI use cases that organizations are exploring (see ‘AI is leading the race for research and innovation’ in Part 1), such as service personalization, influence external-facing services and come with ethical considerations and potential for regulatory scrutiny. If organizations are using AI to customize their offerings or determine who gets access to services based on customer data, they need to be confident their technology is making the right decisions, is free from bias, and doesn’t infringe on consumer rights. This adds to the risk significantly, due to the potential to damage customer trust or lead to regulatory non-compliance.

of CIOs feel there is a ‘moral pressure’ to get AI right.

of CIOs say AI comes with a greater weight of responsibility than other technologies because of its huge potential impact.

of CIOs say the potential pitfalls of AI are huge, so they are proceeding with great caution.

of CIOs say AI is the most high-risk technology that they’ve ever invested in and if anything goes wrong, that burden will be on their shoulders.

The absence of a mature EA function is amplifying this challenge for many organizations. Nearly three-quarters (74%) don’t have an enterprise architecture that provides a full and accurate picture of how AI adoption will impact their ability to comply with regulations such as the forthcoming EU AI Act.

Many (51%) of these organizations are in the process of building an enterprise architecture to achieve the visibility they need, but they are finding it difficult to move fast enough. As a result, nearly half (49%) of CIOs fear there is a risk their company could run into trouble when the EU AI Act or equivalent legislation comes into force.

Organizations are in a race against time to tap into the enormous potential of emerging technologies, such as AI, investing in untested solutions to maintain a competitive edge.

However, while agility and speed to market are key to success, organizations would see greater benefits from emerging technology projects – and fewer risks – by improving their control using up-to-date data and insights. A mature enterprise architecture function is an important part of the solution, providing visibility into current IT infrastructure and helping teams to forecast and track the value delivered by new investments.

With the current focus on AI research, the key for most organizations will be to embed these technologies as an enterprise capability, rather than investing in one-off tools and solutions. Taking a ‘finger in the air’ approach is often the most pragmatic way to get these projects off the ground. However, organizations need to ensure they have mechanisms to mitigate potential pitfalls, learn from initial investments, and maximize the ROI of their AI initiatives.

Five key criteria to successfully manage your AI innovation with a mature EA function

Ultimately, by establishing an enterprise architecture function that delivers these five key criteria, CIOs can make more informed decisions and ensure their investments in emerging technologies are aligned with business outcomes – from growing revenue to reducing risk or lowering costs.

Ardoq is a dynamic, data-driven Enterprise Architecture platform that empowers organizations to navigate change effectively. Recognized as a global leader in the market, Ardoq fuels clear strategic planning, sustainable revenue growth, and repeatable transformation success. Ardoq is a trusted partner for digitally forward organizations seeking to unlock new value and achieve operational excellence.

Slalom is a next-generation professional services company creating value at the intersection of business, technology, and humanity. With a fiercely human approach, they deeply understand their customers—and their customers—to deliver practical, end-to-end solutions that drive meaningful impact. Backed by over 700 technology partners, the nearly 12,000 team members in eight countries and 49 offices help people and organizations dream bigger, move faster, and build better tomorrows for all.