Skip to main content

The Strategic Evolution of IT: From Cost Center to Business Catalyst

Sharon Mandell
Juniper Networks

The perception of IT has undergone a remarkable transformation in recent years. What was once viewed primarily as a cost center has transformed into a pivotal force driving business innovation and market leadership. This shift hasn't just been about changing mindsets — it's about tangible results. Research shows that digital leaders deliver average annual total shareholder returns of 8.1% vs. 4.9% for laggards, highlighting the undeniable link between technological excellence and business success.

As someone who has witnessed and helped drive this evolution, it's become clear to me that the most successful organizations share a common thread: they've mastered the art of leveraging IT advancements to achieve measurable business outcomes. And this mastery isn't accidental — it's the result of deliberate strategies that bridge the traditional gap between technology capabilities and business objectives.

Bridging the Gap Between Technology and Business Objectives

To meaningfully connect technology and business objectives, organizations need practical strategies that move beyond simply acknowledging IT's importance. It's about actively aligning IT initiatives with core business goals, ensuring that technology serves as a catalyst for achieving strategic outcomes. To facilitate this alignment, several approaches should be considered:

Objectives and Key Results (OKRs): OKRs go beyond project and portfolio management by focusing on ambitious, measurable business outcomes that drive progress over time. By aligning their work to these outcomes, tech teams can foster a culture of accountability and transparency, ensuring everyone understands how their work supports overall business goals.

Technology Business Management (TBM): TBM analysis provides transparency into IT investments across the organization. This data-driven approach enables more informed discussions about resource allocation and strategic priorities, shifting conversations from cost control to value creation, while demonstrating IT's direct impact on business success.

Cultivating Cross-Functional Ownership: Breaking down silos between technology teams and other departments is crucial. By establishing dedicated cross-functional teams, aligned to business capabilities, tech professionals can collaborate daily and directly with colleagues from marketing, sales, operations and more. This collaborative approach fosters a deeper understanding of shared goals and ensures that technology solutions are developed with a clear awareness of business needs, allowing for seamless and purposeful integration into existing workflows.

Empowering IT Teams with AI-Native Operations

AI is revolutionizing IT operations, enabling teams to shift focus from routine maintenance to driving strategic business goals. By automating repetitive tasks and delivering real-time insights, AI empowers IT to move from reactive troubleshooting to proactive optimization, reducing distractions and aligning more closely with broader business objectives.

AI-native networking provides a clear example of this transformation, delivering up to 90% fewer trouble tickets and 9x faster deployments. This enables IT teams to reduce downtime, enhance user experiences, and devote more time to initiatives that improve customer engagement, optimize supply chains, and accelerate business growth.

Beyond networking, AI-driven operations represent a broader shift in how IT projects are approached. The traditional model of large-scale, disruptive rollouts is giving way to more agile, iterative strategies. Continuous monitoring and real-time insights allow organizations to adapt technology solutions to evolving business needs, freeing IT professionals to focus on innovation rather than firefighting.

By embracing AI-driven operations, IT teams can become true enablers of business success, helping organizations achieve measurable outcomes and maintain a competitive edge.

Fostering a Culture of Innovation and Collaboration

The most successful organizations recognize that technology-driven transformation requires more than just implementing new solutions — it demands an organization-wide cultural shift. This means evolving IT teams from traditional "order-takers" to influential decision-makers who help shape and execute business strategy. The key lies in creating an environment where innovation thrives and tech professionals feel empowered to contribute their unique perspectives to business discussions.

Organizations must invest in both the technical and business acumen of their IT talent. A dual focus on these areas enables teams to better understand the broader business context of their work and contribute more meaningfully to strategic discussions. When IT professionals can speak the languages of both technology and business, they become invaluable partners in driving broader innovation. Success in this area requires a commitment to continuous learning, mentorship programs and creating opportunities for cross-functional collaboration that expose IT teams to diverse business challenges and perspectives.

The Future of IT Leadership

As we look to the future, the role of IT will continue to evolve. The most successful organizations will be those that anticipate the transformative potential of technology and proactively weave it into the DNA of their strategic blueprints. This means:

  • Forging co-ownership between technology and business leaders
  • Sharing critical data insights across business units to drive better decision-making
  • Maintaining a focus on continuous feedback and adaptation
  • Treating technology investments as strategic assets rather than operational expenses

With technology continuing to reshape industries and markets, the question is no longer whether tech professionals should have a seat at the strategic table, but how to maximize its potential and impact on business success. The answer lies in fostering open dialogue, aligning technology with business objectives and demonstrating tangible value. Now is the time for IT leaders to claim their rightful place at the table, unlocking unprecedented possibilities and paving the way for a new era of success.

Sharon Mandell is SVP and Chief Information Officer at Juniper Networks

The Latest

Pilots are everywhere, stakeholders are seeking results, businesses are pushing for new tools, and IT teams are being asked to make AI secure, reliable, and useful at scale. But as organizations move from testing AI to operationalizing it, many are discovering that the biggest barrier is not the model, the use case, or even the budget. It is the file data foundation within ...

Fast or cheap? For most of my career in engineering, speed and quality sat on opposite ends of a seesaw. The "OR" in "fast or cheap" was non-negotiable. It was expected that pushing for faster releases meant that something in quality would give way. Tightening quality controls meant the schedule slipped. Every engineering leader I know has lived some version of that tradeoff ... The seesaw is starting to level out ...

I have been building enterprise software for more than 20 years ... One thing stays true across all of it: You do not find out your foundation is wrong during the crisis. You find out when the debt comes due. For a lot of organizations, that bill is arriving now. New research ... puts hard numbers on something practitioners have been sensing for a while. The telemetry problem isn't coming. It's already here ...

The rapid growth of AI workloads is pushing traditional log management approaches to their limits, according to The State of Log Management 2026 report from Dynatrace. Modern logs have become critical to understanding, validating, and securing AI-driven decisions, helping organizations ensure reliability, compliance, and performance at scale. However, the volume and complexity of AI telemetry are overwhelming legacy tools ...

For years, secure connectivity has relied on a familiar pattern: route traffic back to centralized gateways, inspect it, and then allow access. This model worked when applications lived in a handful of data centers and users were largely confined to offices. That model is now under strain. Applications are distributed across clouds, users connect from everywhere, and real-time workloads demand performance that centralized inspection points struggle to deliver. As traffic volumes grow and latency expectations shrink, routing everything through a small number of control points has become both a performance bottleneck and a resilience risk. The future of secure connectivity requires a different approach ...

The AI experimentation phase is over, and the private cloud is where enterprise AI workloads are being deployed for security and scale, according to Private Cloud Outlook 2026, a new report from Broadcom ... 2026 marks an acceleration into a full AI tipping point. The shift is being shaped by three forces — costs, complexity, and control — that public cloud environments are increasingly failing to address for production AI at scale. Key findings from the report include ...

44% of organizations have reported an outage in the past year tied to suppressed or ignored alerts, and 78% had at least one incident where no alert was fired at all ... Engineers learned about failures from customers. That gap between what our tools report and what our customers experience is the problem DevOps teams have been quietly solving with GenAI tooling, even as most enterprises continue to run their NOCs on manual alert triage ...

Cloud outages are usually described as technical failures. When a service goes down, a dependency breaks, or a region has issues, the focus immediately shifts to infrastructure. But if you look closely at how these incidents actually unfold, the root cause is rarely the technology itself. It is almost always tied to decisions made earlier, during design, implementation, or day-to-day operations. The system behaves the way it was built. The real question is how it was built ...

77% of leaders say their teams need AI skills urgently. 64% say their organization plans to train current employees rather than hire new ones. So far, so reasonable. The part that surprised me is who's been put in charge: 34% of those leaders say IT and engineering own the AI skills mandate. Learning and Development or HR own it at 7% of organizations. That's roughly five-to-one in favor of the people who understand the tools, over the people whose actual job is teaching adults how to learn new ones ...

In the ever-evolving digital landscape, enterprises are increasingly focused on enhancing their observability stacks to gain deeper insights into their IT environments. Observability has become a cornerstone of modern IT operations, enabling organizations to monitor, diagnose, and optimize their systems with unprecedented precision. However, a critical piece of the puzzle often goes unnoticed in this transformation: IBM i ...

The Strategic Evolution of IT: From Cost Center to Business Catalyst

Sharon Mandell
Juniper Networks

The perception of IT has undergone a remarkable transformation in recent years. What was once viewed primarily as a cost center has transformed into a pivotal force driving business innovation and market leadership. This shift hasn't just been about changing mindsets — it's about tangible results. Research shows that digital leaders deliver average annual total shareholder returns of 8.1% vs. 4.9% for laggards, highlighting the undeniable link between technological excellence and business success.

As someone who has witnessed and helped drive this evolution, it's become clear to me that the most successful organizations share a common thread: they've mastered the art of leveraging IT advancements to achieve measurable business outcomes. And this mastery isn't accidental — it's the result of deliberate strategies that bridge the traditional gap between technology capabilities and business objectives.

Bridging the Gap Between Technology and Business Objectives

To meaningfully connect technology and business objectives, organizations need practical strategies that move beyond simply acknowledging IT's importance. It's about actively aligning IT initiatives with core business goals, ensuring that technology serves as a catalyst for achieving strategic outcomes. To facilitate this alignment, several approaches should be considered:

Objectives and Key Results (OKRs): OKRs go beyond project and portfolio management by focusing on ambitious, measurable business outcomes that drive progress over time. By aligning their work to these outcomes, tech teams can foster a culture of accountability and transparency, ensuring everyone understands how their work supports overall business goals.

Technology Business Management (TBM): TBM analysis provides transparency into IT investments across the organization. This data-driven approach enables more informed discussions about resource allocation and strategic priorities, shifting conversations from cost control to value creation, while demonstrating IT's direct impact on business success.

Cultivating Cross-Functional Ownership: Breaking down silos between technology teams and other departments is crucial. By establishing dedicated cross-functional teams, aligned to business capabilities, tech professionals can collaborate daily and directly with colleagues from marketing, sales, operations and more. This collaborative approach fosters a deeper understanding of shared goals and ensures that technology solutions are developed with a clear awareness of business needs, allowing for seamless and purposeful integration into existing workflows.

Empowering IT Teams with AI-Native Operations

AI is revolutionizing IT operations, enabling teams to shift focus from routine maintenance to driving strategic business goals. By automating repetitive tasks and delivering real-time insights, AI empowers IT to move from reactive troubleshooting to proactive optimization, reducing distractions and aligning more closely with broader business objectives.

AI-native networking provides a clear example of this transformation, delivering up to 90% fewer trouble tickets and 9x faster deployments. This enables IT teams to reduce downtime, enhance user experiences, and devote more time to initiatives that improve customer engagement, optimize supply chains, and accelerate business growth.

Beyond networking, AI-driven operations represent a broader shift in how IT projects are approached. The traditional model of large-scale, disruptive rollouts is giving way to more agile, iterative strategies. Continuous monitoring and real-time insights allow organizations to adapt technology solutions to evolving business needs, freeing IT professionals to focus on innovation rather than firefighting.

By embracing AI-driven operations, IT teams can become true enablers of business success, helping organizations achieve measurable outcomes and maintain a competitive edge.

Fostering a Culture of Innovation and Collaboration

The most successful organizations recognize that technology-driven transformation requires more than just implementing new solutions — it demands an organization-wide cultural shift. This means evolving IT teams from traditional "order-takers" to influential decision-makers who help shape and execute business strategy. The key lies in creating an environment where innovation thrives and tech professionals feel empowered to contribute their unique perspectives to business discussions.

Organizations must invest in both the technical and business acumen of their IT talent. A dual focus on these areas enables teams to better understand the broader business context of their work and contribute more meaningfully to strategic discussions. When IT professionals can speak the languages of both technology and business, they become invaluable partners in driving broader innovation. Success in this area requires a commitment to continuous learning, mentorship programs and creating opportunities for cross-functional collaboration that expose IT teams to diverse business challenges and perspectives.

The Future of IT Leadership

As we look to the future, the role of IT will continue to evolve. The most successful organizations will be those that anticipate the transformative potential of technology and proactively weave it into the DNA of their strategic blueprints. This means:

  • Forging co-ownership between technology and business leaders
  • Sharing critical data insights across business units to drive better decision-making
  • Maintaining a focus on continuous feedback and adaptation
  • Treating technology investments as strategic assets rather than operational expenses

With technology continuing to reshape industries and markets, the question is no longer whether tech professionals should have a seat at the strategic table, but how to maximize its potential and impact on business success. The answer lies in fostering open dialogue, aligning technology with business objectives and demonstrating tangible value. Now is the time for IT leaders to claim their rightful place at the table, unlocking unprecedented possibilities and paving the way for a new era of success.

Sharon Mandell is SVP and Chief Information Officer at Juniper Networks

The Latest

Pilots are everywhere, stakeholders are seeking results, businesses are pushing for new tools, and IT teams are being asked to make AI secure, reliable, and useful at scale. But as organizations move from testing AI to operationalizing it, many are discovering that the biggest barrier is not the model, the use case, or even the budget. It is the file data foundation within ...

Fast or cheap? For most of my career in engineering, speed and quality sat on opposite ends of a seesaw. The "OR" in "fast or cheap" was non-negotiable. It was expected that pushing for faster releases meant that something in quality would give way. Tightening quality controls meant the schedule slipped. Every engineering leader I know has lived some version of that tradeoff ... The seesaw is starting to level out ...

I have been building enterprise software for more than 20 years ... One thing stays true across all of it: You do not find out your foundation is wrong during the crisis. You find out when the debt comes due. For a lot of organizations, that bill is arriving now. New research ... puts hard numbers on something practitioners have been sensing for a while. The telemetry problem isn't coming. It's already here ...

The rapid growth of AI workloads is pushing traditional log management approaches to their limits, according to The State of Log Management 2026 report from Dynatrace. Modern logs have become critical to understanding, validating, and securing AI-driven decisions, helping organizations ensure reliability, compliance, and performance at scale. However, the volume and complexity of AI telemetry are overwhelming legacy tools ...

For years, secure connectivity has relied on a familiar pattern: route traffic back to centralized gateways, inspect it, and then allow access. This model worked when applications lived in a handful of data centers and users were largely confined to offices. That model is now under strain. Applications are distributed across clouds, users connect from everywhere, and real-time workloads demand performance that centralized inspection points struggle to deliver. As traffic volumes grow and latency expectations shrink, routing everything through a small number of control points has become both a performance bottleneck and a resilience risk. The future of secure connectivity requires a different approach ...

The AI experimentation phase is over, and the private cloud is where enterprise AI workloads are being deployed for security and scale, according to Private Cloud Outlook 2026, a new report from Broadcom ... 2026 marks an acceleration into a full AI tipping point. The shift is being shaped by three forces — costs, complexity, and control — that public cloud environments are increasingly failing to address for production AI at scale. Key findings from the report include ...

44% of organizations have reported an outage in the past year tied to suppressed or ignored alerts, and 78% had at least one incident where no alert was fired at all ... Engineers learned about failures from customers. That gap between what our tools report and what our customers experience is the problem DevOps teams have been quietly solving with GenAI tooling, even as most enterprises continue to run their NOCs on manual alert triage ...

Cloud outages are usually described as technical failures. When a service goes down, a dependency breaks, or a region has issues, the focus immediately shifts to infrastructure. But if you look closely at how these incidents actually unfold, the root cause is rarely the technology itself. It is almost always tied to decisions made earlier, during design, implementation, or day-to-day operations. The system behaves the way it was built. The real question is how it was built ...

77% of leaders say their teams need AI skills urgently. 64% say their organization plans to train current employees rather than hire new ones. So far, so reasonable. The part that surprised me is who's been put in charge: 34% of those leaders say IT and engineering own the AI skills mandate. Learning and Development or HR own it at 7% of organizations. That's roughly five-to-one in favor of the people who understand the tools, over the people whose actual job is teaching adults how to learn new ones ...

In the ever-evolving digital landscape, enterprises are increasingly focused on enhancing their observability stacks to gain deeper insights into their IT environments. Observability has become a cornerstone of modern IT operations, enabling organizations to monitor, diagnose, and optimize their systems with unprecedented precision. However, a critical piece of the puzzle often goes unnoticed in this transformation: IBM i ...