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

MEAN TIME TO INSIGHT Podcast - Episode 23: NetOps Labor Shortage

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Why FinOps Rewrote Its Mission and What It Signals for Technology Management

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Clearing the Path to AI: Why Vendor Consolidation Matters Now

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Cold Data, Hot Problem: Why AI Is Rewriting Enterprise Storage Strategy

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

Observability at a Crossroads: AI, Economics, Complexity and the Enduring Power of Open Source

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

Explainability Is the New Battleground in AI-Powered Observability

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

Empowering the Human Side of the Autonomous IT Age

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI Scale Is Outpacing Infrastructure - and IT Leaders Are Running Out of Time

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

No Escalations ≠ No Work: Why Visibility in DevOps Matters More Now That AI Is Accelerating Everything

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...

Observability Costs Rising Faster Than Value

The gap is widening between what teams spend on observability tools and the value they receive amid surging data volumes and budget pressures, according to The Breaking Point for Observability Leaders, a report from Imply ...

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

MEAN TIME TO INSIGHT Podcast - Episode 23: NetOps Labor Shortage

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Why FinOps Rewrote Its Mission and What It Signals for Technology Management

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Clearing the Path to AI: Why Vendor Consolidation Matters Now

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Cold Data, Hot Problem: Why AI Is Rewriting Enterprise Storage Strategy

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

Observability at a Crossroads: AI, Economics, Complexity and the Enduring Power of Open Source

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

Explainability Is the New Battleground in AI-Powered Observability

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

Empowering the Human Side of the Autonomous IT Age

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI Scale Is Outpacing Infrastructure - and IT Leaders Are Running Out of Time

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

No Escalations ≠ No Work: Why Visibility in DevOps Matters More Now That AI Is Accelerating Everything

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...

Observability Costs Rising Faster Than Value

The gap is widening between what teams spend on observability tools and the value they receive amid surging data volumes and budget pressures, according to The Breaking Point for Observability Leaders, a report from Imply ...