2024 AI Predictions - Part 2

With a focus on GenAI, industry experts offer predictions on how AI will evolve and impact IT and business in 2024. Part 2 covers the stakeholders that will drive AI.

Start with: 2024 AI Predictions - Part 1

Go to: predictions about AIOps

Go to: predictions about AI in software development

CHIEF AI OFFICER (CAIO)

We'll see the emergence of new C-suite roles, like Chief AI Officer, who will partner with CIOs to ensure AI adoption continues to grow and emerging regulations are adhered to across the enterprise.
John Cannava
Chief Information Officer, Ping Identity

In 2024, organizations will increasingly appoint leaders to ensure that they are prepared for the security, compliance, and governance implications of AI. As employees become more accustomed to using AI in their personal lives through exposure to tools such as ChatGPT, they will increasingly look to use them in the workplace to boost their productivity. Organizations have already realized that if they don't empower their employees to use these tools officially, they will do so without consent. They will, therefore, appoint a chief AI officer (CAIO) to oversee their use of these technologies in the same way many have a security executive on their leadership teams. The CAIO's role will be centered on developing policies and ensuring the workforce is educated and empowered to use AI safely, to protect the organization from accidental noncompliance, intellectual property leakage, or security threats. This will pave the way for widespread adoption of AI in the enterprise. As this trend progresses, AI will ultimately become a commodity, as the mobile phone has.
Bernd Greifeneder
CTO and Founder, Dynatrace

CTO

The Chief AI Officer will disappear. Rather than the Chief AI officer, the Chief Technology Officer (CTO) will be the natural choice for steering AI strategy. This is not a deprioritization of AI but rather an acknowledgment that AI requires a more cohesive integration to broader technological and business strategies. The CTO will educate and guide the rest of the c-suite on the value of AI, a strategic shift that places AI at the heart of more business decisions.
Prince Kohli
CTO, Automation Anywhere

In 2024, I anticipate the CTO role will evolve as technology leaders will play a central role in fostering collaboration between security and legal departments as AI regulation, legislation, and policy discussions continue to take shape. Drawing on their comprehensive knowledge of the dynamic technology landscape and how technologies can best be harnessed for business success, CTOs have a holistic grasp of the implications of AI deployment, making them instrumental in leading AI regulation discussions. By collaborating with legal and HR teams, CTOs can enhance their organizations' readiness to navigate and comply with emerging AI regulations.
Rob Juncker
CTO, Code42

DATA TALENT

The continued prevalence of AI will lead to an influx of data talent and the need for AI skills. As businesses continue to embrace AI, we're going to see not only an increase in productivity but also an increase in the need for data talent. From data scientists to data analysts, this knowledge will be necessary in order to sort through all the data needed to train these AI models. While recent AI advancements are helping people comb through data faster, there will always be a need for human oversight — employees who can review and organize data in a way that's helpful for each model will be a competitive advantage. Companies will continue looking to hire more data-specific specialists to help them develop and maintain their AI offerings. And those who can't hire and retain top talent — or don't have the relevant data to train to begin with — won't be able to compete.
Brian Peterson
CTO and Co-founder, Dialpad

TECH-SAAVY WORKFORCE

Closing the tech gap — How GenAI is fostering a tech savvy workforce of the future: Throughout history, entry level workers have often been tasked with mundane projects for the first several years of their career. In the near term, we will see many of those early career tasks be automated, freeing up time for entry level employees to spend more time on those "big learning moments" that typically come by being in meetings with leaders and participating in complex, strategic tasks. By empowering entry level workers to do more, they will not only accelerate their career paths, but feel a greater sense of accomplishment and belonging in their roles.
Joe Atkinson
Chief Products and Technology Officer, PwC

AI CONSULTANTS

In the year ahead, there will be consulting services designed to help organizations understand what form of AI is the right AI for their particular needs and specific applications. Not everybody needs the top-of-the-pack GPT-5, if it comes out next year. To determine which AI model is the best match for them, businesses will work with AI experts that provide advice based on their specific use cases to help them keep costs low in the long run. Addressing costs upfront is important because, for POCs, the cost differentials between various AI models are minimal. But as you scale the model to thousands or millions of calls across users, you will pay a hefty price because these models run on costly computer and high-end storage.
Prem Balasubramanian
CTO, Hitachi Digital Services

MANAGED SERVICE PROVIDERS

With the growing technical complexity and tightening budgets, enterprises will increasingly rely on Managed Service Providers (MSPs) to manage and monitor AI technologies. MSPs, with their expertise in AI technologies, will play a key role in spotting errors and ensuring the smooth integration of AI into IT workflows, allowing enterprises to focus on business growth. AI, in turn, will play a crucial role in enhancing network security by providing advanced monitoring, analysis, and error detection capabilities.
Renuka Nadkarni
Chief Product Officer, Aryaka

DIGITAL WORKFORCE

The digital workforce and the human workforce will coincide – Employees across industries are fearful that AI with automate their jobs and displace them. While it's reasonable to suspect that AI will alter jobs (many technological advancements have), in 2024 we'll see that generative AI is making jobs easier and output stronger (companies are already starting to see massive ROI from implementing the new tools). More and more jobs will soon be enhanced by AI —  as it streamlines tasks and offers easy access to knowledge — and employees will find that tedious work has been simplified for them. Rather than replace existing employees, organizations will need to leverage their expertise to determine how new AI tools can best supplement their positions. Over the next few years, businesses and employees will learn to leverage this new "digital workforce" alongside their human workforce, without making the latter feel underutilized or ignored.
Hubert Palan
Founder and CEO, Productboard

Start with: 2024 AI Predictions - Part 3, covering the technologies driving AI.

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When Automating Forever Becomes Faster Than Doing It Once

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Smarter Systems for Disinformation: How Data-Centric Design Could Transform Online Trust

Governments and social platforms face an escalating challenge: hyperrealistic synthetic media now spreads faster than legacy moderation systems can react. From pandemic-related conspiracies to manipulated election content, disinformation has moved beyond "false text" into the realm of convincing audiovisual deception ...

The 5 Pillars of Cross-Platform Observability

Traditional monitoring often stops at uptime and server health without any integrated insights. Cross-platform observability covers not just infrastructure telemetry but also client-side behavior, distributed service interactions, and the contextual data that connects them. Emerging technologies like OpenTelemetry, eBPF, and AI-driven anomaly detection have made this vision more achievable, but only if organizations ground their observability strategy in well-defined pillars. Here are the five foundational pillars of cross-platform observability that modern engineering teams should focus on for seamless platform performance ...

What's Blocking Scalable AI?

For all the attention AI receives in corporate slide decks and strategic roadmaps, many businesses are struggling to translate that ambition into something that holds up at scale. At least, that's the picture that emerged from a recent Forrester study commissioned by Tines ...

Not All Networks Are Built for the Edge

From smart factories and autonomous vehicles to real-time analytics and intelligent building systems, the demand for instant, local data processing is exploding. To meet these needs, organizations are leaning into edge computing. The promise? Faster performance, reduced latency and less strain on centralized infrastructure. But there's a catch: Not every network is ready to support edge deployments ...

Why Observability Is the Missing Piece in Your Business Growth

Every digital customer interaction, every cloud deployment, and every AI model depends on the same foundation: the ability to see, understand, and act on data in real time ... Recent data from Splunk confirms that 74% of the business leaders believe observability is essential to monitoring critical business processes, and 66% feel it's key to understanding user journeys. Because while the unknown is inevitable, observability makes it manageable. Let's explore why ...

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Artificial intelligence is no longer a future investment. It's already embedded in how we work — whether through copilots in productivity apps, real-time transcription tools in meetings, or machine learning models fueling analytics and personalization. But while enterprise adoption accelerates, there's one critical area many leaders have yet to examine: Can your network actually support AI at the speed your users expect? ...

Keeping Your Business Stable When Going Through an IT Disaster

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2024 AI Predictions - Part 2

With a focus on GenAI, industry experts offer predictions on how AI will evolve and impact IT and business in 2024. Part 2 covers the stakeholders that will drive AI.

Start with: 2024 AI Predictions - Part 1

Go to: predictions about AIOps

Go to: predictions about AI in software development

CHIEF AI OFFICER (CAIO)

We'll see the emergence of new C-suite roles, like Chief AI Officer, who will partner with CIOs to ensure AI adoption continues to grow and emerging regulations are adhered to across the enterprise.
John Cannava
Chief Information Officer, Ping Identity

In 2024, organizations will increasingly appoint leaders to ensure that they are prepared for the security, compliance, and governance implications of AI. As employees become more accustomed to using AI in their personal lives through exposure to tools such as ChatGPT, they will increasingly look to use them in the workplace to boost their productivity. Organizations have already realized that if they don't empower their employees to use these tools officially, they will do so without consent. They will, therefore, appoint a chief AI officer (CAIO) to oversee their use of these technologies in the same way many have a security executive on their leadership teams. The CAIO's role will be centered on developing policies and ensuring the workforce is educated and empowered to use AI safely, to protect the organization from accidental noncompliance, intellectual property leakage, or security threats. This will pave the way for widespread adoption of AI in the enterprise. As this trend progresses, AI will ultimately become a commodity, as the mobile phone has.
Bernd Greifeneder
CTO and Founder, Dynatrace

CTO

The Chief AI Officer will disappear. Rather than the Chief AI officer, the Chief Technology Officer (CTO) will be the natural choice for steering AI strategy. This is not a deprioritization of AI but rather an acknowledgment that AI requires a more cohesive integration to broader technological and business strategies. The CTO will educate and guide the rest of the c-suite on the value of AI, a strategic shift that places AI at the heart of more business decisions.
Prince Kohli
CTO, Automation Anywhere

In 2024, I anticipate the CTO role will evolve as technology leaders will play a central role in fostering collaboration between security and legal departments as AI regulation, legislation, and policy discussions continue to take shape. Drawing on their comprehensive knowledge of the dynamic technology landscape and how technologies can best be harnessed for business success, CTOs have a holistic grasp of the implications of AI deployment, making them instrumental in leading AI regulation discussions. By collaborating with legal and HR teams, CTOs can enhance their organizations' readiness to navigate and comply with emerging AI regulations.
Rob Juncker
CTO, Code42

DATA TALENT

The continued prevalence of AI will lead to an influx of data talent and the need for AI skills. As businesses continue to embrace AI, we're going to see not only an increase in productivity but also an increase in the need for data talent. From data scientists to data analysts, this knowledge will be necessary in order to sort through all the data needed to train these AI models. While recent AI advancements are helping people comb through data faster, there will always be a need for human oversight — employees who can review and organize data in a way that's helpful for each model will be a competitive advantage. Companies will continue looking to hire more data-specific specialists to help them develop and maintain their AI offerings. And those who can't hire and retain top talent — or don't have the relevant data to train to begin with — won't be able to compete.
Brian Peterson
CTO and Co-founder, Dialpad

TECH-SAAVY WORKFORCE

Closing the tech gap — How GenAI is fostering a tech savvy workforce of the future: Throughout history, entry level workers have often been tasked with mundane projects for the first several years of their career. In the near term, we will see many of those early career tasks be automated, freeing up time for entry level employees to spend more time on those "big learning moments" that typically come by being in meetings with leaders and participating in complex, strategic tasks. By empowering entry level workers to do more, they will not only accelerate their career paths, but feel a greater sense of accomplishment and belonging in their roles.
Joe Atkinson
Chief Products and Technology Officer, PwC

AI CONSULTANTS

In the year ahead, there will be consulting services designed to help organizations understand what form of AI is the right AI for their particular needs and specific applications. Not everybody needs the top-of-the-pack GPT-5, if it comes out next year. To determine which AI model is the best match for them, businesses will work with AI experts that provide advice based on their specific use cases to help them keep costs low in the long run. Addressing costs upfront is important because, for POCs, the cost differentials between various AI models are minimal. But as you scale the model to thousands or millions of calls across users, you will pay a hefty price because these models run on costly computer and high-end storage.
Prem Balasubramanian
CTO, Hitachi Digital Services

MANAGED SERVICE PROVIDERS

With the growing technical complexity and tightening budgets, enterprises will increasingly rely on Managed Service Providers (MSPs) to manage and monitor AI technologies. MSPs, with their expertise in AI technologies, will play a key role in spotting errors and ensuring the smooth integration of AI into IT workflows, allowing enterprises to focus on business growth. AI, in turn, will play a crucial role in enhancing network security by providing advanced monitoring, analysis, and error detection capabilities.
Renuka Nadkarni
Chief Product Officer, Aryaka

DIGITAL WORKFORCE

The digital workforce and the human workforce will coincide – Employees across industries are fearful that AI with automate their jobs and displace them. While it's reasonable to suspect that AI will alter jobs (many technological advancements have), in 2024 we'll see that generative AI is making jobs easier and output stronger (companies are already starting to see massive ROI from implementing the new tools). More and more jobs will soon be enhanced by AI —  as it streamlines tasks and offers easy access to knowledge — and employees will find that tedious work has been simplified for them. Rather than replace existing employees, organizations will need to leverage their expertise to determine how new AI tools can best supplement their positions. Over the next few years, businesses and employees will learn to leverage this new "digital workforce" alongside their human workforce, without making the latter feel underutilized or ignored.
Hubert Palan
Founder and CEO, Productboard

Start with: 2024 AI Predictions - Part 3, covering the technologies driving AI.

Related Links

Hot Topics

The Latest

When Automating Forever Becomes Faster Than Doing It Once

People want to be doing more engaging work, yet their day often gets overrun by addressing urgent IT tickets. But thanks to advances in AI "vibe coding," where a user describes what they want in plain English and the AI turns it into working code, IT teams can automate ticketing workflows and offload much of that work. Password resets that used to take 5 minutes per request now get resolved automatically ...

Smarter Systems for Disinformation: How Data-Centric Design Could Transform Online Trust

Governments and social platforms face an escalating challenge: hyperrealistic synthetic media now spreads faster than legacy moderation systems can react. From pandemic-related conspiracies to manipulated election content, disinformation has moved beyond "false text" into the realm of convincing audiovisual deception ...

The 5 Pillars of Cross-Platform Observability

Traditional monitoring often stops at uptime and server health without any integrated insights. Cross-platform observability covers not just infrastructure telemetry but also client-side behavior, distributed service interactions, and the contextual data that connects them. Emerging technologies like OpenTelemetry, eBPF, and AI-driven anomaly detection have made this vision more achievable, but only if organizations ground their observability strategy in well-defined pillars. Here are the five foundational pillars of cross-platform observability that modern engineering teams should focus on for seamless platform performance ...

What's Blocking Scalable AI?

For all the attention AI receives in corporate slide decks and strategic roadmaps, many businesses are struggling to translate that ambition into something that holds up at scale. At least, that's the picture that emerged from a recent Forrester study commissioned by Tines ...

Not All Networks Are Built for the Edge

From smart factories and autonomous vehicles to real-time analytics and intelligent building systems, the demand for instant, local data processing is exploding. To meet these needs, organizations are leaning into edge computing. The promise? Faster performance, reduced latency and less strain on centralized infrastructure. But there's a catch: Not every network is ready to support edge deployments ...

Why Observability Is the Missing Piece in Your Business Growth

Every digital customer interaction, every cloud deployment, and every AI model depends on the same foundation: the ability to see, understand, and act on data in real time ... Recent data from Splunk confirms that 74% of the business leaders believe observability is essential to monitoring critical business processes, and 66% feel it's key to understanding user journeys. Because while the unknown is inevitable, observability makes it manageable. Let's explore why ...

Gartner: Regular AI System Assessments Triple the Likelihood of High GenAI Value

Organizations that perform regular audits and assessments of AI system performance and compliance are over three times more likely to achieve high GenAI value than organizations that do not, according to a survey by Gartner ...

Beyond Autoscaling: What True Kubernetes Optimization Actually Requires

Kubernetes has become the backbone of cloud infrastructure, but it's also one of its biggest cost drivers. Recent research shows that 98% of senior IT leaders say Kubernetes now drives cloud spend, yet 91% still can't optimize it effectively. After years of adoption, most organizations have moved past discovery. They know container sprawl, idle resources and reactive scaling inflate costs. What they don't know is how to fix it ...

Is Your Network Ready for the AI Boom? 5 Overlooked Stress Points

Artificial intelligence is no longer a future investment. It's already embedded in how we work — whether through copilots in productivity apps, real-time transcription tools in meetings, or machine learning models fueling analytics and personalization. But while enterprise adoption accelerates, there's one critical area many leaders have yet to examine: Can your network actually support AI at the speed your users expect? ...

Keeping Your Business Stable When Going Through an IT Disaster

The more technology businesses invest in, the more potential attack surfaces they have that can be exploited. Without the right continuity plans in place, the disruptions caused by these attacks can bring operations to a standstill and cause irreparable damage to an organization. It's essential to take the time now to ensure your business has the right tools, processes, and recovery initiatives in place to weather any type of IT disaster that comes up. Here are some effective strategies you can follow to achieve this ...