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AI in 2024: Trends, Challenges and Opportunities

Andreas Grabner

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.

Image removed.
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

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.

Image removed.
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.

Hot Topics

The Latest

Gartner highlighted the six trends that will have a significant impact on infrastructure and operations (I&O) for 2025 ...

Since IT costs can consume a significant share of revenue ... enterprises should (but often don't) pay close attention to the efficiency of IT operations at scale. Improving operational cost structures even fractionally can yield major savings for larger organizations, often in the tens of millions of dollars ...

Being able to access the full potential of artificial intelligence (AI) and advanced analytics has become a critical differentiator for businesses. These technologies allow for more informed decision-making, boost operational efficiency, enhance security, and reveal valuable insights hidden within massive data sets. Yet, for organizations to truly harness AI's capabilities, they must first tap into an often-overlooked asset: their mainframe data ...

The global IT skills shortage will persist, and perhaps worsen, over the next few years, carrying a collective price tag of more than $5 trillion. Organizations must search for ways to streamline their IT service management (ITSM) workflows in addition to, or even apart from, hiring more staff. Those who don't find alternative methods of ITSM efficiency will be left behind by their competitors ...

Embedding greater levels of deep learning into enterprise systems demands these deep-learning solutions to be "explainable," conveying to business users why it predicted what it predicted. This "explainability" needs to be communicated in an easy-to-understand and transparent manner to gain the comfort and confidence of users, building trust in the teams using these solutions and driving the adoption of a more responsible approach to development ...

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