AI, artificial intelligence

Despite a surge in interest among IT professionals to embrace AI technology, significant concerns linger regarding data quality, database infrastructure readiness, and—most critically—security and privacy.

A SolarWinds survey of nearly 700 IT professionals revealed that although nine out of ten IT pros are already using or planning to use AI, these apprehensions are shaping a cautious approach to its adoption.

Krishna Sai, senior vice president of technology and engineering at SolarWinds, said the reality is that the job of IT pros has never been more difficult than it is now.

“Hybrid and multi-cloud environments are increasingly complex and they are only becoming more so,” he said. “That means most IT pros we speak to desperately need AI to help manage their environments.”

He said to successfully integrate AI, organizations must first ensure they have a complete understanding of their data infrastructure.

This requires establishing a comprehensive data governance framework to ensure high-quality data is being used as well as implementing powerful observability solutions, to provide teams with a full-stack view of what’s happening inside a company’s most valuable systems.

Despite the obstacles, the study reflected cautious optimism about AI, with nearly half of IT professionals (46%) wanting their companies to accelerate AI implementation despite costs, challenges, and concerns.

However, just 43% of survey respondents said they are confident that their company’s databases can meet AI’s increased demands–even fewer (38%) trust the quality of data or training used in developing AI technologies.

Sai explained companies can take several steps to ensure they are using high-quality data, including establishment of robust processes for ensuring the quality of training data.

“This includes data cleansing, normalization, and validation to remove inaccuracies, inconsistencies, and biases,” he said.

Organizations can ensure transparency in AI systems by clearly documenting the data sources, algorithms, and decision-making processes.

He said a well-defined machine learning operations (MLOps) pipeline facilitates the demonstration of the rationale behind AI-generated actions, enabling continuous refinement based on evolving needs.

“Ensure that a human is in the loop to regulate AI decisions,” Sai said. “Build in feedback and validation mechanisms so that negative user experiences are properly recorded and addressed.”

More than a third of respondents (38%) reported that their companies already use AI to enhance IT operations’ efficiency and effectiveness, with IT pros identifying AIOps as the AI technology that will have the most significant positive impact on their roles (31%), surpassing LLMs and machine learning.

“The vision for AIOps is optimized performance and improved business outcomes,” Sai said. “With AIOps, companies can identify patterns and anomalies that may signal problems in an IT environment.”

They can quickly correlate huge amounts of data to provide root cause analysis and recommended remediation strategies.

“In turn, this allows IT professionals to improve efficiency and reduce downtime while enriching the lives of individuals and the customers they serve,” Sai said.

Only 38% of respondents expressed strong trust in the data quality and training behind AI technologies, citing data quality as a major barrier to AI adoption, second only to security and privacy risks.

Consequently, today’s IT teams view AI as an advisor (33%) and a sidekick (20%) rather than a solo decision-maker.

Privacy and security concerns were overwhelmingly named as the most significant barriers to AI integration.

When asked about their challenges with AI, four out of ten (41%) respondents reported negative experiences, primarily due to privacy concerns (48%) and security risks (43%).

“Ensuring the privacy and safety of an organization’s data is paramount,” Sai said. “It is critical to ensure that the data used for AI is secure and private, that the right access protections are in place, that any PII data is anonymized before it is used with the LLMs.”

He pointed to the finding that IT pros are advocating for increased government regulations to address security (72%) and privacy (64%).

“This report highlights the promise of AI but also the very real concerns that IT pros have about the technology,” he added.

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