AI in 2024: Trends, Challenges and Opportunities

Andreas Grabner
Learn more about Dynatrace

It's no secret that artificial intelligence (AI) is transforming every aspect of our lives — from healthcare and entertainment to education and business. AI has become central to how organizations drive efficiency, improve productivity, and accelerate innovation.

Conversational generative AI chatbots, such as ChatGPT and Google Bard, can transform the way we work by automating various organizational tasks. Organizations are now recognizing the significant benefits of these technologies when delivering digital services, specifically in development, operations, and security. Generative AI-based solutions allow organizations to automate tasks such as writing software code, creating dashboards, and enabling users to query data through natural language.

Clearly, generative AI will usher in advantages within various industries. However, the technology is still nascent, and according to the recent Dynatrace survey, The state of AI 2024: Challenges to adoption and key strategies for organizational success, there are many challenges and risks that organizations need to overcome to use this technology effectively.


Source: Dynatrace

Organizations Will Accelerate AI Investments

The survey's findings indicate that organizations are already recognizing the vast potential of AI. Nearly two-thirds (61%) of technology leaders say they will increase investment in AI over the next 12 months to speed up software development.

Additionally, survey respondents said AI is benefiting other areas of their organization, too. Other use cases technology leaders identified include enabling business users to easily customize dashboards (54%) and to build interactive queries for analytics (48%). This means AI will affect not only IT and back-office support functions, but also front-line staff in customer-facing roles.

Deploying AI to Reduce Multicloud Complexity

Organizations are building and running millions of applications in the cloud, creating vast amounts of data and complex environments that are difficult to manage. To solve this, technology leaders are turning to AI — 87% of technology leaders say AI-powered issue prevention and remediation are critical to managing multicloud complexity.

Organizations will increase AI investment over the next 12 months to address this complexity by delivering predictable, trustworthy, and precise answers in real time. For example, 73% of technology leaders are investing in AI to generate insight from observability, security, and business events data.

This will create greater productivity among individual teams. DevOps teams, for example, can now focus on strategic projects and innovation instead of tedious manual work. According to the survey, nearly three-quarters of IT operations, development, and security teams plan to use AI to become more proactive in executing their work.

Technology leaders believe AI will also transform the following core DevOps use cases:

■ threat detection, investigation, and response (82%)

■ automating complex operations tasks (63%)

■ eliminating false alerts and the manual effort of validating code deployments (58%)

Minimizing AI Risk Is a Top Priority for Technology Leaders

While the advantages of AI technology are clear, many technology leaders are concerned that generative AI could be susceptible to unintentional bias, error, and misinformation; according to the report, 98% of respondents cited this as a concern. To address this, DevOps teams need to engineer AI prompts that contain detailed context and precision. In doing so, they can achieve meaningful, AI-generated responses that users can trust and avoid inaccurate or inconsistent statements.

Additionally, there are security and compliance risks. According to the survey, 95% of technology leaders are concerned that using generative AI to create code could result in data leakage, as well as improper or illegal use of intellectual property.

AI models must be managed with sufficient guardrails in place to prevent accidental exposure of sensitive information. This will drive demand for purpose-built AI platforms with built-in security and privacy requirements.

AI Will Benefit Employees Throughout Organizations

According to the report, AI will improve workforce satisfaction throughout organizations. Nontechnical workers can make informed, data-driven decisions with easier access to analytics through natural language queries and virtual assistants.

However, to fully take advantage of the benefits of AI, technology leaders agree that a composite AI approach is needed. This entails pairing generative AI with other forms of AI — such as generative, predictive, and causal AI — and different data sources, such as observability, security, and business events. This approach brings precision, context, and meaning to AI outputs. Ultimately, this context enables teams to use this AI-enabled data for better and more efficient decision making.

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AI in 2024: Trends, Challenges and Opportunities

Andreas Grabner
Learn more about Dynatrace

It's no secret that artificial intelligence (AI) is transforming every aspect of our lives — from healthcare and entertainment to education and business. AI has become central to how organizations drive efficiency, improve productivity, and accelerate innovation.

Conversational generative AI chatbots, such as ChatGPT and Google Bard, can transform the way we work by automating various organizational tasks. Organizations are now recognizing the significant benefits of these technologies when delivering digital services, specifically in development, operations, and security. Generative AI-based solutions allow organizations to automate tasks such as writing software code, creating dashboards, and enabling users to query data through natural language.

Clearly, generative AI will usher in advantages within various industries. However, the technology is still nascent, and according to the recent Dynatrace survey, The state of AI 2024: Challenges to adoption and key strategies for organizational success, there are many challenges and risks that organizations need to overcome to use this technology effectively.


Source: Dynatrace

Organizations Will Accelerate AI Investments

The survey's findings indicate that organizations are already recognizing the vast potential of AI. Nearly two-thirds (61%) of technology leaders say they will increase investment in AI over the next 12 months to speed up software development.

Additionally, survey respondents said AI is benefiting other areas of their organization, too. Other use cases technology leaders identified include enabling business users to easily customize dashboards (54%) and to build interactive queries for analytics (48%). This means AI will affect not only IT and back-office support functions, but also front-line staff in customer-facing roles.

Deploying AI to Reduce Multicloud Complexity

Organizations are building and running millions of applications in the cloud, creating vast amounts of data and complex environments that are difficult to manage. To solve this, technology leaders are turning to AI — 87% of technology leaders say AI-powered issue prevention and remediation are critical to managing multicloud complexity.

Organizations will increase AI investment over the next 12 months to address this complexity by delivering predictable, trustworthy, and precise answers in real time. For example, 73% of technology leaders are investing in AI to generate insight from observability, security, and business events data.

This will create greater productivity among individual teams. DevOps teams, for example, can now focus on strategic projects and innovation instead of tedious manual work. According to the survey, nearly three-quarters of IT operations, development, and security teams plan to use AI to become more proactive in executing their work.

Technology leaders believe AI will also transform the following core DevOps use cases:

■ threat detection, investigation, and response (82%)

■ automating complex operations tasks (63%)

■ eliminating false alerts and the manual effort of validating code deployments (58%)

Minimizing AI Risk Is a Top Priority for Technology Leaders

While the advantages of AI technology are clear, many technology leaders are concerned that generative AI could be susceptible to unintentional bias, error, and misinformation; according to the report, 98% of respondents cited this as a concern. To address this, DevOps teams need to engineer AI prompts that contain detailed context and precision. In doing so, they can achieve meaningful, AI-generated responses that users can trust and avoid inaccurate or inconsistent statements.

Additionally, there are security and compliance risks. According to the survey, 95% of technology leaders are concerned that using generative AI to create code could result in data leakage, as well as improper or illegal use of intellectual property.

AI models must be managed with sufficient guardrails in place to prevent accidental exposure of sensitive information. This will drive demand for purpose-built AI platforms with built-in security and privacy requirements.

AI Will Benefit Employees Throughout Organizations

According to the report, AI will improve workforce satisfaction throughout organizations. Nontechnical workers can make informed, data-driven decisions with easier access to analytics through natural language queries and virtual assistants.

However, to fully take advantage of the benefits of AI, technology leaders agree that a composite AI approach is needed. This entails pairing generative AI with other forms of AI — such as generative, predictive, and causal AI — and different data sources, such as observability, security, and business events. This approach brings precision, context, and meaning to AI outputs. Ultimately, this context enables teams to use this AI-enabled data for better and more efficient decision making.

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Manufacturing Organizations Doubled AI Investment Yet Only 37% Fully Prepared to Operationalize AI

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Many organizations rely on cloud-first architectures to aggregate, analyze, and act on their operational data ... However, not all environments are conducive to cloud-first architectures ... There are limitations to cloud-first architectures that render them ineffective in mission-critical situations where responsiveness, cost control, and data sovereignty are non-negotiable; these limitations include ...

The New Perimeter Is the User: Why Identity Is the Real Network Edge

For years, cybersecurity was built around a simple assumption: protect the physical network and trust everything inside it. That model made sense when employees worked in offices, applications lived in data centers, and devices rarely left the building. Today's reality is fluid: people work from everywhere, applications run across multiple clouds, and AI-driven agents are beginning to act on behalf of users. But while the old perimeter dissolved, a new one quietly emerged ...

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For years, infrastructure teams have treated compute as a relatively stable input. Capacity was provisioned, costs were forecasted, and performance expectations were set based on the assumption that identical resources behaved identically. That mental model is starting to break down. AI infrastructure is no longer behaving like static cloud capacity. It is increasingly behaving like a market ...

Enterprise Resilience: Understanding the Shift from Static to Dynamic

Resilience can no longer be defined by how quickly an organization recovers from an incident or disruption. The effectiveness of any resilience strategy is dependent on its ability to anticipate change, operate under continuous stress, and adapt confidently amid uncertainty ...

Mobile Users Expect Perfection in 2026

Mobile users are less tolerant of app instability than ever before. According to a new report from Luciq, No Margin for Error: What Mobile Users Expect and What Mobile Leaders Must Deliver in 2026, even minor performance issues now result in immediate abandonment, lost purchases, and long-term brand impact ...

AI Confidence Is High. Readiness Is Not. What the Data Tells Us - and Why It Matters

Artificial intelligence (AI) has become the dominant force shaping enterprise data strategies. Boards expect progress. Executives expect returns. And data leaders are under pressure to prove that their organizations are "AI-ready" ...

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Agentic AI is a major buzzword for 2026. Many tech companies are making bold promises about this technology, but many aren't grounded in reality, at least not yet. This coming year will likely be shaped by reality checks for IT teams, and progress will only come from a focus on strong foundations and disciplined execution ...

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AI systems are still prone to hallucinations and misjudgments ... To build the trust needed for adoption, AI must be paired with human-in-the-loop (HITL) oversight, or checkpoints where humans verify, guide, and decide what actions are taken. The balance between autonomy and accountability is what will allow AI to deliver on its promise without sacrificing human trust ...

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