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Embracing AI Can Support Business Resiliency During Economic Uncertainty

Ritu Dubey
Digitate

During economic uncertainty, enterprises want improved business uptime, productivity gains, and revenue assurance. To be best positioned to achieve these objectives, it is vital to have a resilient IT and business infrastructure in place. However, with pressure on cost control, reducing and optimizing budgets, companies can't simply hire more support staff, so other optimization avenues need to be explored.

Looking back at previous recessions or economic downturns, investment in technology was one of the first areas to be affected by budgetary cuts and, while it may be tempting for management to look at IT budgets as an area to cut back on for short-term savings, in the long term this can damage a company on a much more fundamental level. Failure to invest in IT could, for example, see an organization left behind technologically while its customers and competitors forge ahead, eroding competitive advantage.

The past few years of the COVID-19 pandemic, which saw business operating models forced to radically shift, and quickly, have helped to demonstrate the importance and value of technology as the backbone of modern business. Investment in technology during this time kept businesses connected, communicating, and operating in the most logistically challenging times. As a result, there is now a greater understanding and appreciation at the management level of what technology brings to the table.

Having said that, of course, investments in IT operations still must show demonstrable business value, especially in testing economic conditions, and that has been historically challenging. In fact, at a November 2022 keynote event in London, Gartner stated that research they conducted found that just 17% of organizations are consistently able to demonstrate the business value of IT. That percentage must improve significantly, and that's where enterprises look to automation to increase IT resilience and optimize performance across the enterprise, without increasing costs. Automating IT tasks can help with business scaling and create sustainable competitive differentiation, which can be a key element during uncertain times.

How AI and AIOps Drive Intelligent Automation

The autonomous enterprise will define the future of corporations, driven in no small part by AI, which enables organizations to streamline and intelligently automate some of the most essential and elemental IT operations tasks, such as monitoring, alerts, root cause analysis, incident management, service request automation such as managing employee onboarding and offboarding. Intelligent automation not only makes organizational IT systems stronger but also frees up skilled IT staff to focus on higher value projects.

By integrating AI and machine learning (ML), enterprises can leverage AIOps to add even more value to IT operations. Embedding historic baseline data, ML works with AI to pull new, deep data from right across an organization as directed, apply intelligent analysis to that data, and add context and meaning. The result is actionable intelligence, which can help management to better understand their business, the economic impact of any downturn, uncover operational inefficiencies and where there may be room for reviews and improvements. As AIOps builds intelligence and knowledge across an organization, it enables proactive and predictive monitoring, so potential problems can be identified and assessed, alerts raised and proactive repairs options given, based on data analysis and historic event profiles and scenarios.

As more enterprises digitize their operations, AIOps are no longer limited to supporting traditional tech workflows, but are now employed across a variety of mainstream business processes, from finance to sales to sourcing and procurement (S&P).

AIOps Delivers Tangible Benefits in Business Performance Monitoring

To illustrate the value of AIOps to an organization, let's consider business performance monitoring. Within today's modern enterprise, business applications and systems, and the supporting IT infrastructure are incredibly complex. Monitoring the health of critical business processes across an organization is vital for seamless business transactions and robust business continuity. As more organizations embrace digital transformation to become fully automated enterprises, historic dependency on labor intensive, inefficient and error-prone manual monitoring and issue resolution is removed. Instead, end-to-end visibility, allied to the correct tools can automatically detect potentially disruptive incidents early and, through AIOps, recommend remedial action. This frees up IT team expertise to focus on higher value, more complicated tasks.

If we look at the retail industry, for example, AIOps is deployed to proactively monitor the performance or health of technology operations across stores, e-commerce sites, and other channels such as mobile apps. Analyzing business processes, applications, middleware, infrastructure, and devices, AIOps applies data analysis, context, and intelligence to automatically detect, visualize, flag, and diagnose anomalies, highlighting root causes and providing automatic resolution of the issues. AIOps can deliver a wealth of benefits to retailers, not only in terms of improved operational KPIs such as Mean-Time-To-Detect, Mean-Time-To-Resolve, time to triage and overall system efficiency, but Business KPI's through optimized inventory, smoother retail operations, improved customer experience and retention, and reduced downtime, leading to higher revenue.

IT Investment is a Multi-faceted Win-Win

The bottom line is that technology is continuously evolving, with AI, ML, automation and cloud-native products and platforms deployed to drive both ROI and positive business outcomes. Strategic investment in IT is really an investment in preparation, business resilience, and advancing competitive positioning. Embracing automation drives the tangible business value of IT operations and encourages the mindset that IT be seen as a business driver as opposed to a cost center. AI and AIOps deliver a wealth of operational improvements, including significantly better system performance and uptime, predictive and preventative intelligence, along with enhanced security and compliance.

The agility and business flexibility that all these technologies provide can help enterprises to better understand challenges, changing market conditions and uncertainty by embedding greater intelligence to decision making through the application of data science, improving efficiencies and better positioning businesses to support future growth — all without breaking the bank.

Ritu Dubey is Global Head of New Business Sales and Market Development at Digitate

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AI observability serves several roles across an organization. AI engineers use it to build, evaluate, and improve AI systems. SREs use it to operate those systems reliably and efficiently in production, including managing their cost. Leaders need it to connect AI behavior and operational performance to business outcomes. The common need is a clear understanding of whether AI systems are delivering the intended result ...

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AI, automation, and enterprise software give organizations an extraordinary amount of leverage. Work that once required hours can happen in minutes. Information buried across systems can be analyzed almost instantly. Complex workflows can be coordinated across teams with far less manual intervention. That leverage creates a temptation to start with the technology ...

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For more than a decade, the default infrastructure play has been simple. Move more workloads to the cloud, retire on-premises gear and treat the data center as a cost to shrink. That logic held while public cloud offered near-limitless capacity at predictable prices, and AI demand is now testing both halves of that assumption ...

Most enterprise IT leaders can tell you exactly how many applications are running across their organization. They can surface a dashboard showing telecom spend by region, pull a report on SaaS license utilization, or call up a real-time view of mobile device inventory. The data is there, and IT leaders have largely delivered on the promise of visibility. Yet, in most organizations, that visibility has not translated into business value ...

Embracing AI Can Support Business Resiliency During Economic Uncertainty

Ritu Dubey
Digitate

During economic uncertainty, enterprises want improved business uptime, productivity gains, and revenue assurance. To be best positioned to achieve these objectives, it is vital to have a resilient IT and business infrastructure in place. However, with pressure on cost control, reducing and optimizing budgets, companies can't simply hire more support staff, so other optimization avenues need to be explored.

Looking back at previous recessions or economic downturns, investment in technology was one of the first areas to be affected by budgetary cuts and, while it may be tempting for management to look at IT budgets as an area to cut back on for short-term savings, in the long term this can damage a company on a much more fundamental level. Failure to invest in IT could, for example, see an organization left behind technologically while its customers and competitors forge ahead, eroding competitive advantage.

The past few years of the COVID-19 pandemic, which saw business operating models forced to radically shift, and quickly, have helped to demonstrate the importance and value of technology as the backbone of modern business. Investment in technology during this time kept businesses connected, communicating, and operating in the most logistically challenging times. As a result, there is now a greater understanding and appreciation at the management level of what technology brings to the table.

Having said that, of course, investments in IT operations still must show demonstrable business value, especially in testing economic conditions, and that has been historically challenging. In fact, at a November 2022 keynote event in London, Gartner stated that research they conducted found that just 17% of organizations are consistently able to demonstrate the business value of IT. That percentage must improve significantly, and that's where enterprises look to automation to increase IT resilience and optimize performance across the enterprise, without increasing costs. Automating IT tasks can help with business scaling and create sustainable competitive differentiation, which can be a key element during uncertain times.

How AI and AIOps Drive Intelligent Automation

The autonomous enterprise will define the future of corporations, driven in no small part by AI, which enables organizations to streamline and intelligently automate some of the most essential and elemental IT operations tasks, such as monitoring, alerts, root cause analysis, incident management, service request automation such as managing employee onboarding and offboarding. Intelligent automation not only makes organizational IT systems stronger but also frees up skilled IT staff to focus on higher value projects.

By integrating AI and machine learning (ML), enterprises can leverage AIOps to add even more value to IT operations. Embedding historic baseline data, ML works with AI to pull new, deep data from right across an organization as directed, apply intelligent analysis to that data, and add context and meaning. The result is actionable intelligence, which can help management to better understand their business, the economic impact of any downturn, uncover operational inefficiencies and where there may be room for reviews and improvements. As AIOps builds intelligence and knowledge across an organization, it enables proactive and predictive monitoring, so potential problems can be identified and assessed, alerts raised and proactive repairs options given, based on data analysis and historic event profiles and scenarios.

As more enterprises digitize their operations, AIOps are no longer limited to supporting traditional tech workflows, but are now employed across a variety of mainstream business processes, from finance to sales to sourcing and procurement (S&P).

AIOps Delivers Tangible Benefits in Business Performance Monitoring

To illustrate the value of AIOps to an organization, let's consider business performance monitoring. Within today's modern enterprise, business applications and systems, and the supporting IT infrastructure are incredibly complex. Monitoring the health of critical business processes across an organization is vital for seamless business transactions and robust business continuity. As more organizations embrace digital transformation to become fully automated enterprises, historic dependency on labor intensive, inefficient and error-prone manual monitoring and issue resolution is removed. Instead, end-to-end visibility, allied to the correct tools can automatically detect potentially disruptive incidents early and, through AIOps, recommend remedial action. This frees up IT team expertise to focus on higher value, more complicated tasks.

If we look at the retail industry, for example, AIOps is deployed to proactively monitor the performance or health of technology operations across stores, e-commerce sites, and other channels such as mobile apps. Analyzing business processes, applications, middleware, infrastructure, and devices, AIOps applies data analysis, context, and intelligence to automatically detect, visualize, flag, and diagnose anomalies, highlighting root causes and providing automatic resolution of the issues. AIOps can deliver a wealth of benefits to retailers, not only in terms of improved operational KPIs such as Mean-Time-To-Detect, Mean-Time-To-Resolve, time to triage and overall system efficiency, but Business KPI's through optimized inventory, smoother retail operations, improved customer experience and retention, and reduced downtime, leading to higher revenue.

IT Investment is a Multi-faceted Win-Win

The bottom line is that technology is continuously evolving, with AI, ML, automation and cloud-native products and platforms deployed to drive both ROI and positive business outcomes. Strategic investment in IT is really an investment in preparation, business resilience, and advancing competitive positioning. Embracing automation drives the tangible business value of IT operations and encourages the mindset that IT be seen as a business driver as opposed to a cost center. AI and AIOps deliver a wealth of operational improvements, including significantly better system performance and uptime, predictive and preventative intelligence, along with enhanced security and compliance.

The agility and business flexibility that all these technologies provide can help enterprises to better understand challenges, changing market conditions and uncertainty by embedding greater intelligence to decision making through the application of data science, improving efficiencies and better positioning businesses to support future growth — all without breaking the bank.

Ritu Dubey is Global Head of New Business Sales and Market Development at Digitate

Hot Topics

The Latest

AI observability serves several roles across an organization. AI engineers use it to build, evaluate, and improve AI systems. SREs use it to operate those systems reliably and efficiently in production, including managing their cost. Leaders need it to connect AI behavior and operational performance to business outcomes. The common need is a clear understanding of whether AI systems are delivering the intended result ...

Part 4 outlines the challenges enterprise face when adopting AI observability. The main challenge is that AI complexity compounds at every stage of maturity. LLM-based applications introduce new behavior, dependencies, and quality considerations, while Agentic AI adds further failure modes as systems make decisions and take actions ...

Part 3 reports on the current state of AI observability. Most experts agree: enterprises are moving faster with AI than they are with the operational discipline needed to run it safely ...

When discussing AI Observability, one of the first questions that arises: Is this just an extension of traditional observability or is this a whole new type of tool? Part 2 compares traditional observability with AI observability ...

In this extensive 14-part series that will post over the next three weeks, experts across observability and AI will provide insight and opinions on the need for AI Observability, the challenges, the benefits, the current state, and predictions for the future ...

Amid rising complexity, organizations are moving quickly toward agent-driven operations: AgenticOps, according to The Impact of Agentic AI on Network Operations, a new report from Cisco ...

AI, automation, and enterprise software give organizations an extraordinary amount of leverage. Work that once required hours can happen in minutes. Information buried across systems can be analyzed almost instantly. Complex workflows can be coordinated across teams with far less manual intervention. That leverage creates a temptation to start with the technology ...

Everyone wants to talk about models. Compute clusters. Benchmark scores that climb a fraction of a point and make headlines anyway. It's an easy conversation to have because it's measurable. But it's also increasingly beside the point ...

For more than a decade, the default infrastructure play has been simple. Move more workloads to the cloud, retire on-premises gear and treat the data center as a cost to shrink. That logic held while public cloud offered near-limitless capacity at predictable prices, and AI demand is now testing both halves of that assumption ...

Most enterprise IT leaders can tell you exactly how many applications are running across their organization. They can surface a dashboard showing telecom spend by region, pull a report on SaaS license utilization, or call up a real-time view of mobile device inventory. The data is there, and IT leaders have largely delivered on the promise of visibility. Yet, in most organizations, that visibility has not translated into business value ...