3 key digital transformation priorities for 2024

The analyst reports tell CIOs that generative AI should occupy the top slot on their digital transformation priorities in the coming year.

Moreover, the CEOs and boards that CIOs report to don’t want to be left behind by generative AI, and many employees want to experiment with the latest generative AI capabilities in their workflows. This year’s technology darling and other machine learning investments have already impacted digital transformation strategies in 2023, and boards will expect CIOs to update their AI transformation strategies frequently. Luckily, many are expanding budgets to do so.

“94% of the executives we surveyed said they had plans to increase their investment in IT or emerging technologies, and 80% said they plan to increase investment in AI over the next year,” reports Ken Englund, leader of technology, media, and telecommunications for the Americas at EY.

Despite all that, CIOs should add generative AI initiatives to the much longer secondary list of transformation programs. After all, every department is pressured to drive efficiencies and is clamoring for automation, data capabilities, and improvements in employee experiences, some of which could be addressed with generative AI. Meanwhile, CIOs must still reduce technical debt, modernize applications, and get cloud costs under control.

As every CIO can attest, the aggregate demand for IT and data capabilities is straining their IT leadership teams. So, before overcommitting to too many priorities, CIOs should reset and review what constitutes a transformational initiative, take steps to avoid hype-inflated goals, and set reasonable priorities with the executive team for the year ahead. Here’s how.

Setting priorities that transform, not just transition

Overwhelming demand for technology capabilities should be met with a keen understanding about the differences between digital transformation and transitionary technology investments. I wrote in Driving Digital, “Digital transformation is not just about technology and its implementation. It’s about looking at the business strategy through the lens of technical capabilities and how that changes how you operate and generate revenues.”

In other words, CIOs should look for investments that impact the business strategy and are force multipliers, impacting both revenue generation and operational efficiencies. Many technology investments are merely transitionary, taking something done today and upgrading it to a better capability without necessarily transforming the business or operating model.

Second, CIOs must identify the gaps between the hype of what business leaders expect from IT departments and the realities. In researching this article, I found gaps where CIOs promised capabilities to stakeholders, but implementations and business impacts have lagged expectations. In many instances, this lag can be anticipated and addressed prior to any commitments.

In considering next year’s priorities, the following initiatives are good bets to be transformational for many organizations, in large part by helping CIOs close execution gaps while delivering ongoing business impacts. 

1. Create these six generative AI workstreams

CIOs should document their AI strategy for delivering short-term productivity improvements while planning visionary impacts. Productivity improvements will likely come from experimenting with the platforms and tools that embed prompting and other natural language capabilities, while longer-term impacts will come from embedding the company’s intellectual property into privately managed large language models.

Many CIOs are already prioritizing generative AI workstreams such as:

1. Experimenting with ChatGPT, copilots, and other tools
2. Evaluating large language models, embeddings, and vector databases
3. Defining generative AI guardrails for the organization, reviewing risks, and translating new regulations

But there are three execution gaps that CIOs should add to these AI workstreams.

First, enterprises have long struggled to improve customer, employee, and other search experiences. Improving search capabilities and addressing unstructured data processing challenges are key gaps for CIOs who want to deliver generative AI capabilities. The 2023 Enterprise Search: The Unsung Hero report found that 98% of organizations say they are improving search capabilities on portals, CRM tools, ecommerce sites, and online communities. But 99% also report technical challenges, listing integration (68%), data volume and cleansing (59%), and managing unstructured data (55% ) as the top three. Closing these gaps while improving search experiences are smart building blocks for facilitating gen AI’s prompting and natural language query capabilities.

The second gap CIOs must address is critical both for results and for credibility. In the 2023 State of Data Science and Machine Learning Report, only 18% of respondents said that at least half their machine learning models make it into production. If CIOs don’t improve conversions from pilot to production, they may find their investors losing patience in the process and culture of experimentation.

Third, in the CDO Agenda: 2024: Navigating Data and Generative AI Frontiers, 57% of respondents haven’t changed their data environments to support generative AI. Not surprisingly, nearly 50% of respondents identified data quality as the top challenge in realizing the potential of generative AI, which requires increasing the scope of dataops and data governance programs to include unstructured data sources and defining where to apply them in LLM experiments.

These workstreams require documenting a vision, assigning leaders, and empowering teams to experiment. CIOs should look to set realistic goals and communicate which workstreams are priorities.

2. Drive business impacts by closing operational and security gaps

Digital transformations aim to deliver competitive advantages typically through new digital products, improved customer experiences, and data-driven decision-making. Initiatives vary by industry and business strategy and may include smart manufacturing, digital health, e-government initiatives, sustainability programs, digital twins, and others.

Underpinning these initiatives are digital transformation core competencies, which include design thinking, product management, agile methodologies, devops practices, citizen development, and data governance. These practices include leadership and delivery practices backed by operational and risk management competencies, and it’s these competencies where research shows many organizations are lagging. CIOs should consider where closing these gaps falls in their digital transformation priorities.

For example, over the past decade, many CIOs promoted devops practices such as CI/CD, infrastructure as code, data observability, and closing the cultural gaps between development teams and IT operations. In the DevOps Benchmarking Study 2023, top performers realize significant business benefits, including 67% with on-demand deployment frequency and 94% with change failure rates under 15%.

But while many organizations call it devsecops, implementing devsecops security best practices is lagging, according to other surveys.   

In the SANS 2023 DevSecOps Survey, less than 22% of respondents patched and resolved critical security risks and vulnerabilities in under two days. And while static application security testing (SAST) was the top-rated tool for usefulness by 82% of respondents, only 28% claim these tools are used on at least 75% of their code base.

Here, the State of DevSevOps in 2023 report highlights several gaps CIOs should focus on closing in their 2024 digital transformations, including inadequate security training, shortages of application security personnel, and lack of transparency in development and operations workflows.  

CIOs should look for other operational and risk management practices to complement transformation programs. For example, McKinsey estimates enterprises can cut 15% to 20% of cloud costs through optimizations, and implementing finops practices is one opportunity. Another area to focus on is continuous testing, especially as generative AI and copilots can increase the velocity of code development and risks from code generators.  

3. Develop transformation leaders to drive more initiatives

The increasing demand for innovation, enterprise-wide transformation, and departmental technology, data, and automation capabilities is a significant challenge for CIOs today. It’s fairly common to see more technology investment requests than there are program managers, architects, and other leaders with roles in transformation initiatives. Add on the backlog of technical debt, security improvements, and work to transform shadow IT, and that’s one overcommitted IT department.

While not all these initiatives fit my definition of digital transformation, being able to oversee more initiatives, standardize multi-use platforms, and provide governed citizen data science programs can be highly transformative. The transformation is driven by developing more digital transformation leaders, or what I call digital trailblazers.

Gartner’s top priority for HR in 2024 is leader and manager development, given that HR leaders report that 76% of managers are overwhelmed by the growth of their job responsibilities, and juggle 51% more responsibilities than they can handle. I suspect many CIOs struggle with these same issues within their departments, especially when asking digital trailblazers to lead and contribute to too many initiatives.

To address this, CIOs should partner with HR, tap into their training and development budgets, and initiate programs to develop transformation and change management leaders. Doing so will help CIOs increase the number of initiatives IT can launch, while delivering results faster and reducing the organization’s friction to change.

As CIOs look into 2024, prioritizing the right balance of initiatives in their digital transformation programs will be challenging. Keep in mind that overpromising and underdelivering are recipes for failure, so increasing the number of digital transformation leaders and investing in learning programs are key for CIOs facing pressure to deliver greater and faster impacts.