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14 CIO priorities and trends for 2024

The job is as big and challenging as ever. In 2024, CIOs will be asked to find business value in GenAI, mitigate AI risks and solve the talent crunch, among other pressing issues.

Generative AI will be the top technology trend in 2024 and a priority for CIOs tasked by boards with vetting new tools, provisioning infrastructure, preparing for new risks and taking advantage of new user experiences.

This will not be easy since most vendors are adding new GenAI capabilities, often with significant costs. CIOs will need to work out the business cases for these tools to determine if they can deliver real value or result in a costly failure.

The impact of generative AI on CIOs will go far beyond new generative AI tools and infrastructure itself. CIOs may also be tasked with upgrading data infrastructure and processes, budgeting for new cybersecurity tools, as well as attracting new talent, upskilling teams and redeploying staff freed up by more efficient processes.

Outside of generative AI, CIOs will also increasingly play a role in vetting the ROI of cloud infrastructure, consolidating warehouse automation infrastructure and mulling the value of new digital twin tools.

Here is a rundown on how these various trends will impact CIO priorities in 2024.

Generative AI

1. Delivering value from GenAI hinges on collaborating with business teams

Tilak Doddapaneni, executive vice president and global head of engineering at Publicis Sapient, said that finding the business value of generative AI will be a top priority for CIOs, no easy task given how fast the technology is evolving.

Headshot photo of Tilak Doddapaneni, global head of engineering, Publicis SapientTilak Doddapaneni

"CIOs are facing a predictable yet critical challenge, with their foremost priority being to comprehend and collaborate with business teams to grasp the impact of generative AI," he said.

CIOs will need to work closely with business teams to discern the applications of GenAI, facilitate the provision of necessary tools and platforms, and strategize the business cases and costs associated with its implementation.

One key aspect will lie in creating architectural abstractions that shield systems from the rapid evolution in the AI space. CIOs will also need to cultivate a deep understanding of the costs associated with these advancements.

Headshot photo of Yugal Joshi, partner, Everest GroupYugal Joshi

2. Volatility of AI spurs use of platforms offering embedded GenAI

Some firms will continue to experiment with and sometimes even scale GenAI initiatives. But more enterprises will turn to their existing platforms such as ServiceNow, SAP, Salesforce and Microsoft for simplicity and speed, said Yugal Joshi, partner at Everest Group, an advisory firm. There is too much volatility in AI tools right now for most CIOs to want to invest in.

One big concern will be the pricing uplift platform vendors are asking. In some cases, their GenAI offerings are 200% more expensive than their other products and services, said Joshi. On the flip side, these vendors are also starting to offer indemnity protection that could help ease concerns about new liabilities.

3. New GenAI risks require a review of governance frameworks, corporate culture

As enterprises rush into generative AI, CIOs will increasingly be tasked with addressing risks that must be managed. Scott Laliberte, managing director and global leader at Protiviti's Emerging Technology Group, said it will be imperative for CIOs to set appropriate expectations and ROI predictions.

Headshot photo of Scott Laliberte, managing director, ProtivitiScott Laliberte

They will need to ensure new use cases align with the overall business strategy by partnering with key business executives. They may also be involved in establishing a solid AI governance framework. It will be imperative for CIOs to foster an ongoing culture of innovation, emphasizing the symbiotic relationship between AI and human capabilities to build trust and drive the adoption of the new tools.

4. GenAI spurs rethink of UX and UI strategies

CIOs will also need to understand UX and UI requirements for internal and external stakeholders.

"The conventional notion of UI is undergoing a paradigm shift, especially for platforms utilizing GenAI, which demands a significant rethink of UX strategies," Doddapaneni said. Diverse approaches to UI are essential since many types of interaction don't fit into a chatbot model.

Data

5. Data engineering and data architecture required for GenAI tasks

Doddapaneni predicts that 60% to 70% of the upcoming tasks to address generative AI needs will revolve around data engineering. CIOs will need to establish a core data architecture. They will also need to develop processes for formatting data appropriately, placing it in suitable locations for model training, ensuring data version accuracy and evaluating the current state of data platforms such as data warehouses and customer data platforms.

Headshot photo of Nick Kramer, vice president of applied solutions, SSA & CompanyNick Kramer

6. Data management and governance take center stage

Nick Kramer, leader of applied solutions at global consulting firm SSA & Company, predicts that despite the generative AI headlines and hype, AI adoption will continue to be slow. In this current climate, the most innovative CIOs will focus on data management and governance. These CIOs recognize that curating high-quality data, bringing in unstructured data under management and establishing data literacy need to come first. These efforts can often be justified within innovation budgets while driving immediate impact through visibility, knowledge-sharing and better decision-making.

Cybersecurity

7. AI-amplified cyberthreats require bigger security budgets, new tactics

AI will amplify threat actor tactics, techniques and procedures in 2024. Stephen Ross, head of business development, Americas at S-RM, a global corporate intelligence and cybersecurity consultancy, predicts this will increase the rate of highly targeted spear phishing, simplify fraud attacks and drive vishing (voice phishing).

Headshot photo of Stephen Ross, head of business development, Americas at S-RMStephen Ross

Ross is concerned that the average cybersecurity budget only grew 1% in the U.S. last year while threat actors are evolving much more rapidly. Security tools that were effective five years ago are now ineffective, and even vendors that seemed bulletproof have been compromised. "CIOs need to bang the table at budget time to fight for the critical technological updates their organization needs to stay ahead of the threat actors," said Ross.

8. Cybersecurity alignment with business goals is of top importance

Aligning cybersecurity strategies with overall business imperatives will remain a priority for CIOs in 2024 as the challenges of balancing risk management with operational efficiency continue, according to Andrew Morrison, principal at Deloitte Risk & Financial Advisory.

Headshot photo of Andrew Morrison, principal at DeloitteAndrew Morrison

"While the execution of cyber programs often falls to the CISO or head of information security, the CIO will need to align with cyber as part of their overall business strategy, which can often be a challenge, especially as the pace of digital transformation increases," Morrison said.

As organizations push more data to the edge, increase their cloud dependency and embrace advanced technologies like generative AI to enable growth, they may also create new vulnerabilities that attackers can use to compromise their systems. CIOs who prioritize a security-by-design approach in their own strategies while also applying that thinking to new tech implementations will be well-positioned to help their organizations achieve competitive advantage in the years to come.

Talent

9. IT talent concerns require close collaboration with HR and talent acquisition teams

John King, partner in the business transformation practice of Lotis Blue Consulting, predicts that CIOs in 2024 will need to prioritize upgrading, managing and retaining key talent in their organizations. Technology trends in cybersecurity, AI, cloud migration and digital transformation all require very different and upgraded skills. Without significant upskilling and reskilling efforts, the ROI on new technology projects will be deficient, leading to slower uptake from the business.

Success will require working closely with HR, workplace learning and talent acquisition teams to align on the investments needed to upgrade existing employee skills and bring in new capabilities. These investments will be significant.

Headshot photo of John King, partner, Lotis Blue ConsultingJohn King

"If IT is not viewed by the company as a highly strategic asset, those conversations will have to happen sooner than later, as upskilled staff will be highly attractive to poachers if not kept engaged and compensated," King said.

Bringing in new resources with the right profiles will likely be more expensive than previous IT hires. Over time, implementing technologies like generative AI for code writing and integrations will reduce the number of overall people needed in IT, but total costs may remain close to the same.

Once these programs are launched, CIOs also need to ensure that their people remain engaged and motivated by their work and that they are not at risk for flight, especially given the increased investment being made in their careers. Working with HR will be critical to developing an approach that monitors the health of the IT organization, pinpoints areas where there is a risk of departure and can quickly make interventions to retain employees.

10. Workforce learning programs and talent management accelerate

Stephen Watt, CIO at Hyland, a content management platform, predicts that workforce management will be a key trend for CIOs as they broker the adoption of new technology in 2024, including new AI systems that require both employee training and participation.

Headshot photo of Stephen Watt, CIO, HylandStephen Watt

Enterprises will continue to find new and innovative ways to shorten labor gaps with intelligent, customized AI interactions and processes. Still, they will need access to skills in their team members who can build them.

"We need to be ramping up our own AI skills, both within our technical teams … and within our business groups so they, too, can understand where and how these technologies may have the most impact," Watt said.

Generative AI is a transformational technology, but the transition to GenAI systems and processes still requires people to make it work. "Our job as leaders will be to ensure we can train, retain and compete for the best people who grow this skill set, and I think that will be the trend that will take the most time and effort, more than the technology itself," Watt said.

11. Boards push CIOs to rethink engineering talent deployment and headcounts

Conversely, CIOs will also have to plan for GenAI-driven productivity boosts in coding processes and impact on the software engineering lifecycle. Joshi predicts board members will push CIOs to rethink the IT talent model, the headcount needed to build and run their systems, new roles and skills required, and chart out GenAI-centric career paths for individuals.

"This will be a daunting task for the CIOs and they will need to understand talent implications more deeply than earlier technology disruptions" Joshi said.

GenAI-related productivity increases might free up talent for areas like cybersecurity that have been perennially understaffed. "Every CIO complains about it but can't do anything about it, as they don't have the funding," Joshi said. He predicted that boards will ask CIOs to use GenAI to ameliorate these talent problems.

Infrastructure

12. Warehouse interoperability comes of age

CIOs in physical product and logistics companies will increasingly prioritize their tech stacks for warehouse automation. Historically, automation solutions have been difficult to integrate as they tend not to speak the same language and require complex customized code to integrate everything together.

Headshot photo of Rowan Stott, research analyst, Interact AnalysisRowan Stott

"We're now seeing more systems being developed with open interfaces, as well as interoperability platforms like SVT Robotics that make it far easier to integrate and connect systems together," said Rowan Stott, research analyst at advisory firm Interact Analysis. He said CIOs should be looking at how they can develop a more interoperable technology stack that makes it easier to take advantage of innovations in robotics and conveyance systems to streamline operations and reduce costs.

13. Cloud cost discussions will emphasize ROI

CIOs are increasingly getting pulled into discussions about inflated cloud bills. Everest Group has found that 87% of clients are dissatisfied with the value they are getting from cloud adoption. Joshi predicts that cost discussions in 2024 will increasingly focus on ROI.

Enterprises will want their cloud providers and tech services partners to build ROI models to show their cloud adoption journey and estimate an ROI positive timeline, how much investments will be needed upfront and yearly, and the number of cloud workloads they need to migrate to get to the positive.

14. AI democratizes physics-based simulation

While generative AI seems to be getting all the press this year, innovations in physics-based simulations and digital twins could play an essential role in building products, democratizing formerly expensive and complicated tools. (A physics simulation is computer-based modeling that uses mathematical equations to replicate real-world behaviors.) For example, in late 2023, Google researchers demonstrated a new weather simulation model running on a single machine for a few minutes that previously required hours on dozens of machines. CIOs could be tasked with determining the cost-benefit ratio of this pairing and associated infrastructure and training.

Headshot photo of Christian Buckner, senior vice president, AltairChristian Buckner

Christian Buckner, senior vice president of data analytics and IoT at Altair, expects more enterprises to combine AI with physics simulation. Physics models can sometimes take a lot of computer power and time, while AI is limited by the historical data available. As these tools mix and match, they will bring the best of both worlds while reducing limitations.

"Increasingly, we will see physics models sped up with AI, AI models trained on synthetic data from physics models, and simulation user workflows sped up by natural language interfaces," said Buckner. The result will be faster, more accurate iterations that require significantly less compute cost and less user effort.

George Lawton is a journalist based in London. Over the last 30 years he has written more than 3,000 stories about computers, communications, knowledge management, business, health and other areas that interest him.

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