• It's clear that artificial intelligence remains a focal point for investments, but technology leaders need to be careful not to neglect other areas.
• Cybersecurity and data privacy are components of IT that are never out of vogue and demand sufficient funding.
• Companies should continue to invest in AI solutions, but in many cases with a more discerning approach.

With a little over four months left in 2024, where should companies be allocating their IT budgets for the remainder of the year? It's clear that artificial intelligence remains a focal point for investments, but technology leaders need to be careful not to neglect other areas.

Here are some key areas that CIOs and other tech executives should focus on, according to experts.

Protecting the safety and privacy of data is a component of IT that is never out of vogue and that demands sufficient funding.

"Cyber threats continue to evolve, and as digital transformation accelerates, so does the potential for cyberattacks," said Christopher Gilchrist, principal analyst at research firm Forrester.

"With the increase in remote work, cloud adoption, and IoT devices, the attack surface for cyber threats has expanded significantly," Gilchrist said. "Regulatory compliance requirements are also becoming more stringent across industries, necessitating investments in robust cybersecurity frameworks and compliance tools."

Allocating budgets to enhance cybersecurity measures, such as implementing zero-trust architectures, upgrading firewalls, and adopting advanced threat detection systems, can protect companies from costly breaches and ensure they meet regulatory obligations, Gilchrist said.

Creating a 'future-fit' enterprise

"Expectations for value from information technology investments have shifted quite a bit from just 'drive operational excellence,'" said Janelle Hill, vice president and analyst at research firm Gartner. "Today, the dominant expectation is to use technology to optimize business outcomes."

To that end, enterprises need to leverage modern, digital technologies to drive growth and business expansion, Hill said. "Budget for IT must continue to focus on modernizing existing applications and moving to the cloud," she said. "A lot of that continues. However, they should be investing more in market-facing and 'middle office' initiatives rather than back office, shared services."

Most of Gartner's business executive clients tell the firm they want to be able to respond faster and more easily to shifting market dynamics. "This is not just reacting, but proactively looking to capitalize on emerging opportunities," Hill said.

Business capability models (also called business capability maps), provide graphical representations of all business capabilities within an organization, their relationship to one another, and hierarchy.

"What most enterprises are missing in their modernization efforts is making investments that enable them to lower the cost, time and risk of changing how they operate," Hill said. "I refer to this as becoming future-fit — ready for any disruption or opportunity."

Becoming future fit requires moving away from investments in process automation and moving toward modular redesign of business capabilities, Hill said. "Few have mastered the art of designing discrete modular capabilities that can be reused and reassembled — like Legos — to create new designs to meet the needs of different scenarios and opportunities."

CIOs need to deconstruct business processes into the critical activities performed every day to add business value. "A business capability model is a key visual that can be used as a tool to facilitate investment decisions," Hill said.

Critical cloud optimization tools

Cloud computing remains a critical enabler of scalability, flexibility, and cost-efficiency, Gilchrist said. "However, many organizations are now moving from cloud adoption to cloud optimization," he added.

This involves fine-tuning cloud infrastructure to reduce waste, optimize costs, and ensure efficient use of resources.

"Investments in multi-cloud strategies, cloud-native applications, and tools for monitoring and managing cloud environments can help companies achieve better performance and cost savings," Gilchrist said. "Additionally, companies should consider investing in cloud security to protect their cloud assets from emerging threats."

Data analytics and decision-making

In the digital economy, data is gold. Those organizations that leverage data and data analytics well can improve the customer experience and move out in front of competitors.  

"Data-driven decision-making is increasingly becoming a competitive differentiator," Gilchrist said. "By investing in data analytics and business intelligence tools, companies can harness the power of their data to gain actionable insights, improve operational efficiency, and enhance customer experiences."

With advancements in data analytics, companies can take advantage of real-time data processing, predictive analytics, and AI-powered analytics to make informed decisions quickly, Gilchrist said. "Budget allocations should focus on enhancing data infrastructure, upgrading analytics platforms, and training staff to use these tools effectively," he said.

AI, as needed

Yes, companies should continue to invest in AI solutions, but in many cases with a more discerning approach.

"Rather than investing in AI for the sake of innovation, companies should prioritize AI projects that align with their strategic goals and offer clear, measurable ROI," Gilchrist said. "AI investments should focus on areas where automation, predictive analytics, or AI-driven insights can solve specific business problems or create new revenue streams."

There is a risk of overinvesting in AI without a clear understanding of its potential impact or the readiness of the organization to adopt it, Gilchrist said. "Companies should avoid pouring money into AI initiatives without first establishing a solid foundation, such as data quality, infrastructure, and skilled personnel, to support these technologies."

As AI becomes more pervasive, ethical considerations around data privacy, bias, and transparency are gaining attention. "Companies should allocate budgets to ensure their AI initiatives are ethical, transparent, and compliant with evolving regulations," Gilchrist said.