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The Challenge of 2024: Potential Benefits and Risks from Adopting AI

Alastair Pooley
Snow Software

Generative AI has recently experienced unprecedented dramatic growth, making it one of the most exciting transformations the tech industry has seen in some time. However, this growth also poses a challenge for tech leaders who will be expected to deliver on the promise of new technology. In 2024, delivering tangible outcomes that meet the potential of AI, and setting up incubator projects for the future will be key tasks.

There can be no doubt that AI software can augment human capabilities to increase productivity and efficiency, which can have an impact on most industries, even highly regulated ones; the opportunity for increased productivity is too great to ignore. The challenge facing many organizations is how to invest in such innovation at a time where pressure on funding remains high.


Productivity Impact

To deliver value in 2024, finding the right pilot projects which harness the power of AI is key. The main use cases today include replacing customer service interactions, summarizing reports, writing personalized marketing content, language translation or generating software code. These areas have solutions already in the market and may represent easy wins that can be shown to deliver outcomes. However, looking at which fundamental changes can bring the most benefit to any organization will take time. While companies are quickly making massive strides forward thanks to AI, these will be the exceptions rather than the norm. Many external vendors are also looking to provide updated service offerings as they make use of AI, and these will likely also lead to productivity gains.

Increased Cybersecurity Risk

According to Snow Software's IT Priorities Report, cybersecurity remains, as it has for many years, a continuing top priority for leaders. In 2024, the only issue more important for IT leaders than cybersecurity is AI and there can be no doubt that sophistication in attacks, particularly those that trick people using social engineering, is only going to increase with new AI-driven powers. Typical cybersecurity training will struggle to be relevant in the face of voicemails using deepfake technology to flawlessly reproduce a leader's voice or phishing emails perfectly written and tailored to the recipient. It should also be expected that fabricated videos will become more prevalent. This will require leaders to enter an arms race of increasing protection to meet the increased level of threats. It is likely that security spending will have to continue to grow during 2024.

Budgetary Implications

Most IT leaders are facing budget pressure, and most have encountered numerous examples of SaaS vendors implementing substantial price increases in 2023 (my personal experience was one supplier who sought to increase prices by 160%). The effects of inflation, rising supplier and vendor costs, and new AI-based services will impact IT budgets, requiring leaders to find innovative ways to cope within constraints.

Consolidating your IT estate is one method of reducing budget pressure. This trend was mirrored in the IT Priorities Report, where 88% of IT leaders reported moving towards platforms and away from point tools. Reducing licenses and rightsizing use are also key for finding room within budgets. This is where IT asset management (ITAM) practices, with the right tools in place, are essential for organizations looking to save on costs. Between cloud, SaaS, unused or over-provisioned licenses and the overall increased complexity within IT environments at most organizations, a significant amount of waste is essentially guaranteed.

This is especially true for the many organizations that have recently undergone mass layoffs or mergers and acquisitions. There are significant opportunities for organizations to save on costs when undergoing transitions, and the insight provided through ITAM could help save significant costs.

The AI Implication for Cloud Costs

The growing usage of public cloud has led to the emergence of the FinOps movement, which is a discipline focused on managing cloud resources effectively. With AWS adopting the FinOps standard, the adoption of FinOps practices and certifications is expected to increase rapidly. Every large organization will have at least one employee working on FinOps practices, with enterprise adoption being the strongest. The larger the cloud bill, the more necessary FinOps will become.

With the rise of AI, we will consume more CPU power, which will drive up cloud bills and add complexity. FinOps strategies, along with ensuring the presence of appropriate business units at the table, will be key for organizations to ensure their cloud spending is constrained to what the company needs.

What's Next?

The next step in the AI journey is likely to be regulation, of both the technology itself and the data that powers it. The speed at which governments have already produced proposed frameworks is indicative of the importance policy makers place on ensuring AI technologies do not operate without guardrails. To maximize beneficial outcomes from transformative technology, we need space for innovation to thrive. It is therefore critical that governments strike the correct balance between safety and innovation, which ensure we can reap the benefits without losing privacy, and whilst protecting intellectual property.

Alastair Pooley is CIO of Snow Software

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The Challenge of 2024: Potential Benefits and Risks from Adopting AI

Alastair Pooley
Snow Software

Generative AI has recently experienced unprecedented dramatic growth, making it one of the most exciting transformations the tech industry has seen in some time. However, this growth also poses a challenge for tech leaders who will be expected to deliver on the promise of new technology. In 2024, delivering tangible outcomes that meet the potential of AI, and setting up incubator projects for the future will be key tasks.

There can be no doubt that AI software can augment human capabilities to increase productivity and efficiency, which can have an impact on most industries, even highly regulated ones; the opportunity for increased productivity is too great to ignore. The challenge facing many organizations is how to invest in such innovation at a time where pressure on funding remains high.


Productivity Impact

To deliver value in 2024, finding the right pilot projects which harness the power of AI is key. The main use cases today include replacing customer service interactions, summarizing reports, writing personalized marketing content, language translation or generating software code. These areas have solutions already in the market and may represent easy wins that can be shown to deliver outcomes. However, looking at which fundamental changes can bring the most benefit to any organization will take time. While companies are quickly making massive strides forward thanks to AI, these will be the exceptions rather than the norm. Many external vendors are also looking to provide updated service offerings as they make use of AI, and these will likely also lead to productivity gains.

Increased Cybersecurity Risk

According to Snow Software's IT Priorities Report, cybersecurity remains, as it has for many years, a continuing top priority for leaders. In 2024, the only issue more important for IT leaders than cybersecurity is AI and there can be no doubt that sophistication in attacks, particularly those that trick people using social engineering, is only going to increase with new AI-driven powers. Typical cybersecurity training will struggle to be relevant in the face of voicemails using deepfake technology to flawlessly reproduce a leader's voice or phishing emails perfectly written and tailored to the recipient. It should also be expected that fabricated videos will become more prevalent. This will require leaders to enter an arms race of increasing protection to meet the increased level of threats. It is likely that security spending will have to continue to grow during 2024.

Budgetary Implications

Most IT leaders are facing budget pressure, and most have encountered numerous examples of SaaS vendors implementing substantial price increases in 2023 (my personal experience was one supplier who sought to increase prices by 160%). The effects of inflation, rising supplier and vendor costs, and new AI-based services will impact IT budgets, requiring leaders to find innovative ways to cope within constraints.

Consolidating your IT estate is one method of reducing budget pressure. This trend was mirrored in the IT Priorities Report, where 88% of IT leaders reported moving towards platforms and away from point tools. Reducing licenses and rightsizing use are also key for finding room within budgets. This is where IT asset management (ITAM) practices, with the right tools in place, are essential for organizations looking to save on costs. Between cloud, SaaS, unused or over-provisioned licenses and the overall increased complexity within IT environments at most organizations, a significant amount of waste is essentially guaranteed.

This is especially true for the many organizations that have recently undergone mass layoffs or mergers and acquisitions. There are significant opportunities for organizations to save on costs when undergoing transitions, and the insight provided through ITAM could help save significant costs.

The AI Implication for Cloud Costs

The growing usage of public cloud has led to the emergence of the FinOps movement, which is a discipline focused on managing cloud resources effectively. With AWS adopting the FinOps standard, the adoption of FinOps practices and certifications is expected to increase rapidly. Every large organization will have at least one employee working on FinOps practices, with enterprise adoption being the strongest. The larger the cloud bill, the more necessary FinOps will become.

With the rise of AI, we will consume more CPU power, which will drive up cloud bills and add complexity. FinOps strategies, along with ensuring the presence of appropriate business units at the table, will be key for organizations to ensure their cloud spending is constrained to what the company needs.

What's Next?

The next step in the AI journey is likely to be regulation, of both the technology itself and the data that powers it. The speed at which governments have already produced proposed frameworks is indicative of the importance policy makers place on ensuring AI technologies do not operate without guardrails. To maximize beneficial outcomes from transformative technology, we need space for innovation to thrive. It is therefore critical that governments strike the correct balance between safety and innovation, which ensure we can reap the benefits without losing privacy, and whilst protecting intellectual property.

Alastair Pooley is CIO of Snow Software

Hot Topics

The Latest

For years, production operations teams have treated alert fatigue as a quality-of-life problem: something that makes on-call rotations miserable but isn't considered a direct contributor to outages. That framing doesn't capture how these systems fail, and we now have data to show why. More importantly, it's now clear alert fatigue is a symptom of a deeper issue: production systems have outgrown the current operational approaches ...

I was on a customer call last fall when an enterprise architect said something I haven't been able to shake. Her team had just spent four months trying to swap one AI vendor for another. The original plan said three weeks. "We didn't switch vendors," she told me. "We rebuilt half our integrations and discovered what we'd actually been depending on." Most enterprise leaders don't expect that to be the experience ...

Ask any senior SRE or platform engineer what keeps them up at night, and the answer probably isn't the monitoring tool — it's the data feeding it. The proliferation of APM, observability, and AIOps platforms has created a telemetry sprawl problem that most teams manage reactively rather than architect proactively. Metrics are going to one platform. Traces routed somewhere else. Logs duplicated across multiple backends because nobody wants to be caught without them when something breaks. Every redundant stream costs money ...

80% of respondents agree that the IT role is shifting from operators to orchestrators, according to the 2026 IT Trends Report: The Human Side of Autonomous IT from SolarWinds ...

40% of organizations deploying AI will implement dedicated AI observability tools by 2028 to monitor model performance, bias and outputs, according to Gartner ...

Until AI-powered engineering tools have live visibility of how code behaves at runtime, they cannot be trusted to autonomously ensure reliable systems, according to the State of AI-Powered Engineering Report 2026 report from Lightrun. The report reveals that a major volume of manual work is required when AI-generated code is deployed: 43% of AI-generated code requires manual debugging in production, even after passing QA or staging tests. Furthermore, an average of three manual redeploy cycles are required to verify a single AI-suggested code fix in production ...

Many organizations describe AI as strategic, but they do not manage it strategically. When AI plans are disconnected from strategy, detached from organizational learning, and protected from serious assumptions testing, the problem is no longer technical immaturity; it is a failure of management discipline ... Executives too often tell organizations to "use AI" before they define what AI is supposed to change. The problem deepens in organizations where strategy isn't well articulated in the first place ...

Across the enterprise technology landscape, a quiet crisis is playing out. Organizations have run hundreds, sometimes thousands, of generative AI pilots. Leadership has celebrated the proof of concept (POCs) ... Industry experience points to a sobering reality: only 5-10% of AI POCs that progress to the pilot stage successfully reach scaled production. The remaining 90% fail because the enterprise environment around them was never ready to absorb them, not the AI models ...

Today's modern systems are not what they once were. Organizations now rely on distributed systems, event-driven workflows, hybrid and multi-cloud environments and continuous delivery pipelines. While each adds flexibility, it also introduces new, often invisible failures. Development speed is no longer the primary bottleneck of innovation. Reliability is ...

Seeing is believing, or in this case, seeing is understanding, according to New Relic's 2025 Observability Forecast for Retail and eCommerce report. Retailers who want to provide exceptional customer experiences while improving IT operations efficiency are leaning on observability ... Here are five key takeaways from the report ...