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How Digital Enterprises Can Navigate the Technological Landscape in 2024

Prithika Sharone
ManageEngine

In the dynamic business landscape, success is not an achievement but an ongoing journey. Once heavily reliant on streamlining manual operations and physical communications, organizations adapted as the digital revolution unfolded, embracing transformative technologies to sustain themselves and maintain success.
Today, as enterprises transcend into a new era of work, surpassing the revolution, they must shift their focus and strategies to thrive in this environment. Here are five key areas that organizations should prioritize to strengthen their foundation and steer themselves through the ever-changing digital world.

1. Elevated priority on privacy and AI governance

Although 2023 has witnessed numerous regulations across geographies — including the California Consumer Privacy Act, the EU's AI Act, the UAE's Data Protection Act, and India's Digital Personal Data Protection Act — the implementation of similar policies across various regions is imminent. With AI being integrated into many aspects of business, disruptive technologies (such as deepfakes and augmented reality) threaten privacy and pose significant risks. To ensure ethical, transparent, and fair use of the technology, AI governance should be paramount to businesses. Privacy must be ingrained into the core of every business going forward, and protecting it should become the responsibility of every individual in the organization.

2. Adopting purpose-built LLMs

Ever since the advent of AI, businesses have leveraged its capabilities to fulfill predictive analysis and automate low-level tasks. However, the narrow applications of AI and its immense engineering difficulties call for AI training models that can cater to all aspects of a business. Enterprise-focused large language models (LLMs) help both employees and customers alike achieve deep-nested conversations with the enterprise's offerings and align better with evolving software tools. Adapting such models is imperative for enterprises to deploy their vast amount of knowledge to address both their creative and redundant workloads. It empowers organizations to protect their data, reduce biases in their data, and provide detailed audit reports to understand AI decisions.

3. Enterprise-wide orchestration

More recently, businesses have turned to digital transformation to carry out their core functions online. This transition has presented the challenge of fragmentation — splitting data into organizational silos and hampering the flow of information. Enterprises can overcome the issue of fragmentation by harnessing the power of orchestration, which allows the construction of interconnected digital pipelines that lead to workflow automation and streamlined operations. Adopting this user-friendly and accessible technology prepares organizations to make complex tasks achievable and survive in the digital realm.

4. Evolution to a secure digital-first experience

Moving on from traditional work methodologies, organizations must integrate contemporary IT management tools to provide a holistic and safe digital journey. In 2024, enterprises should also adopt an identity-centric approach, ensuring that only authorized individuals are granted access and permissions to organization resources, thus safeguarding their identities and data. Going a step further, cloud infrastructure and entitlement management (CIEM) must be implemented to increase granular visibility and minimize threats through the comprehensive view of identities and entitlements provided across diverse cloud environments. Together, identity-centric management and CIEM solutions will bolster security and enable a worry-free digital experience for end users.

5. Cyber resilience as a business differentiator

Today's technological landscape presents a series of challenges for modern companies that stunt progress. These challenges include the geopolitical climate, technological disruption, cyberthreats, competitive pressure, and many other factors, all of which could be more easily faced when strategic plans are in place. In 2024, companies should look to actively adopt plans that foster the tools, solutions, and culture necessary to enhance their overall cyber-resiliency posture. Consequentially, cyber resilience must emerge as a key business differentiator, enabling organizations to succeed in the complex global market. These five concepts are crucial pillars of the modern digital landscape and can help enterprises navigate the rising number of IT challenges. By being attuned to such technological advancements, organizations increase their chances of innovating better, delivering responsibly, fortifying their defenses, and anchoring their presence in the market for not just this year but many more to come.

Prithika Sharone is an Enterprise Analyst at ManageEngine

The Latest

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

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

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 ...

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 ...

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 ...

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 ...

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 ...

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 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.

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 ...

How Digital Enterprises Can Navigate the Technological Landscape in 2024

Prithika Sharone
ManageEngine

In the dynamic business landscape, success is not an achievement but an ongoing journey. Once heavily reliant on streamlining manual operations and physical communications, organizations adapted as the digital revolution unfolded, embracing transformative technologies to sustain themselves and maintain success.
Today, as enterprises transcend into a new era of work, surpassing the revolution, they must shift their focus and strategies to thrive in this environment. Here are five key areas that organizations should prioritize to strengthen their foundation and steer themselves through the ever-changing digital world.

1. Elevated priority on privacy and AI governance

Although 2023 has witnessed numerous regulations across geographies — including the California Consumer Privacy Act, the EU's AI Act, the UAE's Data Protection Act, and India's Digital Personal Data Protection Act — the implementation of similar policies across various regions is imminent. With AI being integrated into many aspects of business, disruptive technologies (such as deepfakes and augmented reality) threaten privacy and pose significant risks. To ensure ethical, transparent, and fair use of the technology, AI governance should be paramount to businesses. Privacy must be ingrained into the core of every business going forward, and protecting it should become the responsibility of every individual in the organization.

2. Adopting purpose-built LLMs

Ever since the advent of AI, businesses have leveraged its capabilities to fulfill predictive analysis and automate low-level tasks. However, the narrow applications of AI and its immense engineering difficulties call for AI training models that can cater to all aspects of a business. Enterprise-focused large language models (LLMs) help both employees and customers alike achieve deep-nested conversations with the enterprise's offerings and align better with evolving software tools. Adapting such models is imperative for enterprises to deploy their vast amount of knowledge to address both their creative and redundant workloads. It empowers organizations to protect their data, reduce biases in their data, and provide detailed audit reports to understand AI decisions.

3. Enterprise-wide orchestration

More recently, businesses have turned to digital transformation to carry out their core functions online. This transition has presented the challenge of fragmentation — splitting data into organizational silos and hampering the flow of information. Enterprises can overcome the issue of fragmentation by harnessing the power of orchestration, which allows the construction of interconnected digital pipelines that lead to workflow automation and streamlined operations. Adopting this user-friendly and accessible technology prepares organizations to make complex tasks achievable and survive in the digital realm.

4. Evolution to a secure digital-first experience

Moving on from traditional work methodologies, organizations must integrate contemporary IT management tools to provide a holistic and safe digital journey. In 2024, enterprises should also adopt an identity-centric approach, ensuring that only authorized individuals are granted access and permissions to organization resources, thus safeguarding their identities and data. Going a step further, cloud infrastructure and entitlement management (CIEM) must be implemented to increase granular visibility and minimize threats through the comprehensive view of identities and entitlements provided across diverse cloud environments. Together, identity-centric management and CIEM solutions will bolster security and enable a worry-free digital experience for end users.

5. Cyber resilience as a business differentiator

Today's technological landscape presents a series of challenges for modern companies that stunt progress. These challenges include the geopolitical climate, technological disruption, cyberthreats, competitive pressure, and many other factors, all of which could be more easily faced when strategic plans are in place. In 2024, companies should look to actively adopt plans that foster the tools, solutions, and culture necessary to enhance their overall cyber-resiliency posture. Consequentially, cyber resilience must emerge as a key business differentiator, enabling organizations to succeed in the complex global market. These five concepts are crucial pillars of the modern digital landscape and can help enterprises navigate the rising number of IT challenges. By being attuned to such technological advancements, organizations increase their chances of innovating better, delivering responsibly, fortifying their defenses, and anchoring their presence in the market for not just this year but many more to come.

Prithika Sharone is an Enterprise Analyst at ManageEngine

The Latest

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

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

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 ...

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 ...

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 ...

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 ...

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 ...

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 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.

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 ...