CIO Priorities

Despite uncertain economic conditions, investing in generative AI is on the minds of executives around the globe, according to KPMG data.  

Nearly 3 in 4 CEOs say generative AI is a top spending priority, according to the survey of 1,300 CEOs at large companies globally, including 400 in the U.S. 

Executives expect the technology to bring increased profitability, new products, market growth opportunities, enhanced innovation and aid cybersecurity efforts, according to the report. 

Generative AI has captured the attention of top executives as they pursue the economic upside to the technology. While generative AI is expected to reach across departments, CIOs and other technology executives are helming the efforts.

“My goal is to help introduce the new technology, to provide more context around what it is and to provide education around the technology,” Justin Skelton, SVP and CIO at Dine Brands Global, said. 

The company which operates Applebee’s, IHOP and Fuzzy’s Taco Shop, is taking a prudent approach to generative AI adoption, thinking through how data is stored and retained as well as defining clear principles and values for acceptable use.

The strategy also calls for taking responsibility for the technology, according to Skelton. "That means building those partnerships with other members of the organization to make sure that, when we do implement it, we do it the right way with the right requisite controls on it,” Skelton said.

Successful implementation can prove challenging, but with the proper foundation, technology leaders can forge ahead. For organizations further along in the adoption process, the focus for CIOs then becomes finding real value from implementation.

Nearly two-thirds of CEOs say they expect to see a return on their investment in three to five years. Fewer — less than one-third — expect a faster ROI of one to three years, according to KPMG data.

Technology priorities dominate the C-suite priority list as economic concerns begin to ease, according to a PwC survey. The study polled 609 senior U.S. executives during the first week of August.

Nearly 3 in 5 executives plan to invest in new technologies over the next 12 to 18 months, according to the study. Generative AI investments are a top business priority for nearly half of executives, PwC found. 

Despite interest in adoption, finding measurable value in new technology investments represents a challenge for nearly all executives. The cost of deploying new technologies is also a hurdle for more than 4 in 5 business leaders. 

Hype and headlines aside, enterprise executives are still in the early stages of understanding exactly how generative AI supports broader business goals.

"What we're finding on a consistent basis is that almost every company across every sector is doing an inward analysis of how generative AI impacts their companies, both on an efficiency standpoint, and on a growth standpoint," said Neil Dhar, U.S. vice chairman and consulting co-leader at PwC.

Most organizations right now are focused on bringing management teams together and identifying which areas, from backend tasks to more customer-facing processes, stand to gain from generative AI adoption, Dhar said.

Unsurprisingly, the assessment found the CIO is the most optimistic member of the C-suite when it comes the emerging technology.

More than 4 in 5 CIOs believe generative AI will support new business models within their units over the next year and a half. Overall, just two-thirds of C-suite members share that belief.

Despite ambitious plans for adoption and investments, the technology is still nascent in the eyes of most leaders, who remain concerned over the risks of plugging generative AI into their organizations.

More than half of leaders say generative AI brings cybersecurity risk and potential inaccuracies, according to a McKinsey survey published Aug. 1. Though risks are a top concern, just one-third of organizations have processes in place to lower security risk.

CIOs have doubled down on modernizing enterprise data systems to ease AI adoption, as the computing demands of the technology pose a challenge to adoption ambitions. 

Most technology executives expect their organizations to increase investments in data infrastructure and AI adoption over the next year, according to an MIT Technology Review report commissioned by Databricks. All 600 CIOs and IT leaders surveyed in the report said data and AI budgets will grow over the next year, and nearly half anticipate a boost of more than 25%.

The initial barrier to entry for generative AI adoption is low, but the barrier to productionize the technology remains high, Naveen Zutshi, CIO at Databricks, said. “Right now, when digging deeper, you find more experiments and less production use cases,” Zutshi said.

As eager organizations greenlight pilot programs and task innovation teams with developing generative AI business applications, CIOs are refining the fuel that drives the emerging technology — data.

Despite efforts to streamline architecture, unlock silos and integrate disparate sources, data ecosystems often succumb to entropy over time.

“It's not that organizations want to be complex,” Zutshi said. “They become complex because there were legacy systems and there were decisions made over time that resulted in that complexity. Unwinding is not easy.”

Hybridizing AI strategy

From a data standpoint, experimenting with off-the-shelf models available via cloud marketplaces and SaaS solutions is a relatively easy lift. But most organizations favor a hybrid AI strategy, leveraging available tools for immediate use cases while tuning and training models on internal data, the report found.

More than half of respondents — 58% — said they are open to both building and buying the technology. While only slightly more than 1 in 10 are solely focused on engineering their own tools, just 3 in 10 were content with commercial models.

Databricks has teams building foundational models for customers. The company is also leveraging available technologies for enterprise use cases, primarily for internal chatbots to assist in customer support, contract reviews and job descriptions, according to Zutshi.

“Building a foundation model costs hundreds of thousands or millions of dollars and only a small number of companies will do it,” said Zutshi.

Most organizations will take the middle path, using internal data to tune off-the-shelf models for specific tasks. The primary lever for feeding an LLM external data, a process known as retrieval-augmented generation, creates risk and opportunity.

“Companies have a lot of unstructured data stored somewhere that they do very little with,” Zutshi said, pointing to information stored across platforms such as Confluence and Google Drive or in PDF form.

Generative AI can ingest data from these sources, surfacing previously buried insights. But most organizations are new to the idea of using unstructured data without first putting it in a structured database, so there will be a learning curve, Zutshi said.

Data first

Laying the foundation for generative AI requires upfront investment.

“Just moving landlocked data can be a pretty gargantuan exercise,” Zutshi said. “These problems don’t go away because you have generative AI.”

Even organizations that have been relatively proactive in data operations can require remediation, as technologies and strategies have evolved rapidly.

“Data infrastructure that worked five years ago doesn’t work now,” Murali Brahmadesam, CTO and head of engineering at financial services company Razorpay, said in the report.

Zutshi said he had a data warehouse coupled with on-prem databases and a cloud-based data lake five years ago, when he served as CIO at Palo Alto Networks. Data duplication and separate access rules for data science and analytics teams contributed to operational complexity.

“Until a few years ago, we weren’t talking about lakehouses,” said Zutshi. “We were using data warehouses and they tended to put data in separate silos. We built systems based on that paradigm and now that paradigm has changed.”

Incremental migration and integrations that show value to the business can remove resistance.

“If I told my CEO that I was going to spend the next 18 months fixing my data foundation, but there won’t be any immediate returns, I would be laughed out of the room,” said Zutshi.

Enthusiasm for generative AI may buy CIOs some time. According to a KPMG survey of 1,300 CEOs, most expect ROI to arrive in three to five years, not tomorrow or the next day.

Nearly one-third of IT leaders said integrating AI was the top priority in 2023, according to Snow Software’s IT Priorities survey of 800 IT decision-makers. Security risk mitigation and IT cost reduction were also high on the CIO agenda. 

Budget concerns traversed tech categories, the report found. Around one-quarter of respondents said cloud services, security tools, hardware, on-prem software and SaaS applications were a major source of overspending. One in 5 IT leaders said they were already spending too much on generative AI tools like ChatGPT and Bard.

“There is no business as usual for IT leaders today,” Alastair Pooley, CIO at Snow Software, said in a release accompanying the report. “Between navigating challenging economic conditions and the emergence of game-changing technologies like generative AI, the role of IT is in flux.”

IT leaders see opportunities for future cost reduction in many of the same places they’ve increased spending. 

Tech investments increased in several broad categories this year. Three-quarters of respondents increased spending on security tools, and slightly fewer on SaaS applications. Two-thirds poured more into cloud infrastructure and services, the report said.

But more doesn’t always equate to better, especially when it’s not clear where the money is going or what it is accomplishing. Two-thirds of IT leaders indicated business units procure far more cloud and SaaS than IT departments realize. 

Tech leaders and CIOs know the lack of visibility is a problem worth solving, but its complexity makes it challenging, according to the report. From cybersecurity protocols to a lack of resources or skills, there’s not just one answer CIOs cited as the problem in the report. 

The pressure to gain better visibility into spending and usage is expected to expand as organizations push for innovation and adopt generative AI tools, the report said, as IT leaders may find funding shifting to emerging technologies.

“The complexity of technology seems to grow exponentially every year, making it vital for IT leaders to address this issue relatively quickly or be at risk of being left behind,” the report said.

CIOs expect larger budgets for cybersecurity, data analytics and cloud platforms next year as demand for democratized IT capabilities grows, according to a Gartner survey published Monday. 

With increased technology, CIOs are primarily pursuing improved customer or citizen experiences, according to the analyst firm. Gartner consulted nearly 2,500 CIOs for its annual study, which the firm presented at the Gartner IT Symposium/Xpo in Orlando, Florida. 

“As CIOs are expected by their CEO to orchestrate a range of enterprise outcomes, CIOs must integrate and align the digital initiatives led by their CxO counterparts," said Janelle Hill, distinguished VP analyst at Gartner, in a statement. "CIO and CXO co-ownership of digital delivery is an indivisible part of enterprise – not just functional – outcome attainment.”

CIOs spent most of 2023 tracking the impact of economic woes on their businesses and industries. Next year, leaders will focus on two priorities: keeping companies safe from threat actors and enabling advanced technologies across the organization. 

With nearly three quarters of CIOs planning to increase investments into AI next year, the challenge will be to link those capabilities to improved customer experiences, the top outcome executives are aiming for. 

Closely behind improved customer experiences is the goal of expanding operating margins, a top-three priority for more than half of CIOs. AI's role in augmenting worker efficiency, and how exactly the technology can deliver, is one of Gartner's critical trends to watch into 2024.

Adoption, however, is still a work in progress.

Though 70% of CIOs refer to generative AI as a game-changing technology, just 9% of CIOs have deployed it in their enterprises. More than half say they have plans to deploy generative AI in the next two years.

Gartner urged CIOs Monday to put in place strategies around generative AI, given its potential for deep transformation. 

“There will be all sorts of unforeseen consequences,” said Mary Mesaglio, distinguished VP analyst at Gartner, speaking Monday at Gartner IT Symposium/Xpo 2023. “What this means is that you need to think ahead of time about what lines you won’t cross.”

The wild ride of 2023, a year ripe with major technology and business shifts, is in its final months. Companies now have their sights set on 2024, setting expansion goals and preparing to pursue them.

While CEOs have always expected IT leaders to accelerate growth with technology, next year will emphasize the CIO's ability to augment their company’s capabilities, especially as economic and geopolitical issues pressure executives.

"There's a lot of pressure," said Matt Guarini, VP, senior research director at Forrester. "I think that folks feel like a lot of the CEOs are turning on them and saying 'now is your time to deliver.'"

Businesses have high expectations for AI, but it's still hard to attract talent and manage geopolitical and regulatory issues.

Here are five Forrester predictions CIOs and other technology leaders can use to guide their decisions next year.

1. Most technology executives will fall short on growth plans

Even the most direct mandates to use tech for growth will fail if a company is not clear on what growth actually looks like. Forrester expects just 1 in 10 tech leaders will get growth right despite clear calls to action from CEOs.

There's still a disconnect between systems and people that can derail businesses trying to grow in 2024, according to the firm.

"We still see too much divergence between tech strategy and business strategy," Guarini said. 

Too often, tech units build new capabilities based on their own views, rather than responding to business needs, he said. This will lead to delayed project delivery times and budget overruns.

2. The generative AI boost is coming 

Generative AI evolved from an abstract notion to a concrete capability across several IT functions this year. Businesses have gradually started to use the technology to their advantage,accelerating software delivery and aiding IT help desk support.

In 2024, workers will continue to organically infuse the tech into their daily work, and organizations will improve their ability to roll out new features, drawn in by the potential productivity gains, Forrester said. 

Thanks to enterprise AI initiatives, companies will be able to boost productivity and creative problem-solving by 50%, according to the analyst firm.

"[Companies are] gonna have to put guidelines around it, no doubt," said Guarini. As adoption rolls forward, companies will benefit from employees' ability to automate repetitive tasks and identify new ways to work.

3. Leaders look to shadow HR 

The big layoff cycles hitting the tech sector earlier this year did little to solve the long-standing challenge of attracting tech skills. With the development of generative AI, companies will need even more workers in specialized categories such as data engineers.

The rapid pace at which tech skills turn over will lead businesses to rely more closely on "shadow HR" next year, as external partners provide support to backfill critical skills. The firm expects 20% of leaders to rely on these partners for their talent needs.

"The best organizations will stay close to their HR business partners," said Guarini. However, some businesses will need to work with partners to get what they need in terms of tech capabilities.

4. CIOs tap partners for AI success

Large professional services firms, from PwC to Accenture and EY, have aggressively invested to deliver generative AI capabilities for clients in the past year. Development efforts have included the creation of in-house models, training programs and the internal roll-out of tools to their employees.

The growth of this ecosystem means most tech execs will seek partners to close the AI gap, as half of businesses will fail to master it internally.

Forrester expects more businesses to turn to services firms in their push to close the AI skills gap and add new features to products and services. But overreliance on partners can mean internal skill building is neglected.

"We are seeing that, in some cases, companies are losing a lot of their ability to do things, because they become so reliant on going to the service partners to get capabilities and jobs done," said Guarini. "We can see that people are going to use it to close the gap. But, if you don't build these capabilities internally, you're going to struggle in the long run." 

5. Geopolitical pressures mount

The effects of geopolitical unrest, ongoing shifts in regulation and other challenges will push two-thirds of businesses to reassess their approach to tech operations, according to the analyst firm. 

While in recent years organizations have pushed their companies to a global operating model, the rising regulation will impact technology and operating decisions, according to Guarini.

Executives will need to mull questions as they arise, Guarini said. "If I'm going to be using these large language models, can I use them in China? Probably not," Guarini said. "How do I think about how GDPR is going to affect how I update it?"