3 ways to align leadership and maintenance teams for AI success

Organizations are increasingly leveraging artificial intelligence (AI) to analyze critical asset data and help make strategic maintenance decisions that impact both day-to-day operations and long-term organizational plans. Smart vibration sensors and software are connecting more assets to systems, allowing organizations to collect more data than ever before. With AI and predictive maintenance (PdM), companies can leverage new technologies to experience improved operational efficiency and reliability. 

As technologies evolve, an aligned vision for maintenance between senior decision-makers and maintenance managers is crucial for long-term profitability and routine operations. But while assets are becoming more connected, a recent Fluke Reliability survey revealed a startling disconnect between senior decision-makers and maintenance managers as to whether AI could be beneficial for their plants, and how it should be used. 

This difference underscores the need for enhanced training, pilot programs, and cross-functional teams to align priorities and ensure effective AI integration across organizational levels.

Misalignment in current and future maintenance methods

The misalignment between executives and maintenance managers is on display even when discussing current maintenance strategies. The research, conducted by Censuswide, surveyed over 600 senior decision-makers and maintenance professionals in the U.S., the UK, and Germany. Key survey results include:

• Almost half (45%) of senior decision-makers said their organizations currently use a reactive maintenance strategy, compared to under 3 in 10 (28%) of maintenance managers who said the same. 
• Almost two-thirds (63%) of maintenance managers said they currently use a proactive maintenance strategy, compared to under half (46%) of executives.
• And when it comes to the idea of using industrial AI to augment human capabilities with predictive maintenance in the future, over a fifth (23%) of executives said they would prefer to use a predictive maintenance strategy. Only 15% of maintenance managers agreed.

The survey also uncovered that investing in AI is a big priority for most leaders, regardless of level. Over half of senior decision-makers and two-thirds of maintenance managers said they planned to invest in AI in the next 23 months. And overall, 93% of respondents said that AI would be beneficial in facing key industry challenges in 2024 and beyond. 

Most respondents agree industrial AI is worth the investment and would benefit their organizations. But to ensure the entire organization can maximize the benefit of AI integration, managers and executives must have an aligned, strategic vision for how AI can be integrated into everyday processes and the impact it can have on overall organizational strategy.

Three ways to align AI integration strategies

Executives and maintenance managers often have competing priorities about how to integrate AI into their operations. Senior decision-makers may want to leverage AI to improve organizational clarity, using it to perform tasks like data cleansing between systems to assist in better decision-making. 

On the other hand, maintenance managers may be more interested in using AI to analyze equipment information, assist with predictive maintenance using vibration sensors, or uncover maintenance blind spots with advanced analytics. For example, when a maintenance team is struggling to identify the root cause of a problem, they can use AI to look across an entire asset database and identify similarities in previous cases to find potential answers to their current problem.

Effective change management starts with getting executives and maintenance managers aligned on priorities and implementation strategies. This can be done through enhanced training, pilot programs, and developing a cross-functional team to guide the integration process.

Enhanced training. AI integration is a high-level strategic initiative. When considering making such sweeping changes, C-suite leaders often focus on long-term ROI, competitive advantage, and overall business growth. Training tailored for executives can emphasize AI’s role in predictive maintenance, cost reduction, and operational efficiency. These sessions should focus on real-world stories, KPIs, and financial outcomes to help executives see how integrating AI will align with corporate goals.

For maintenance managers, training should focus on the practical aspects of AI, such as how it will improve day-to-day operations, reduce downtime, and enhance predictive maintenance capabilities. Demonstrating how AI tools can make maintenance teams more efficient will also foster buy-in and trust.

Pilot programs. Pilot programs can be a powerful tool for getting C-suite executives and maintenance managers aligned on AI goals. A small-scale rollout of AI technologies allows C-suite executives to see a controlled implementation without committing large-scale resources. This low-risk approach validates ROI and productivity improvements and helps visualize the operational efficiencies gained.

Pilot programs give maintenance teams the opportunity to test AI tools in a real-world environment. This assures maintenance managers that the technology is practical and applicable to their role. It also allows maintenance team members to see how introducing AI would impact their existing workflows.

A small initial rollout allows both parties to track KPIs to provide tangible metrics for future decision-making. It builds trust between the two groups and gives everyone an opportunity for hands-on learning in a low-stakes environment.

Cross-functional teams. Building a cross-functional team also helps align priorities between C-suite executives and maintenance managers when integrating AI into plants. This team should be made up of key stakeholders from various roles and levels of leadership that will ensure a well-rounded approach to AI deployment, addressing both strategic and operational needs.

A cross-functional team brings together C-suite executives, maintenance managers, IT specialists, data scientists, and other relevant personnel to collaborate on AI initiatives. This shared ownership ensures everyone is working toward common goals, such as improving plant efficiency, reducing downtime, and boosting profitability.

Executives can bring a high-level, business-driven perspective, while maintenance managers can contribute operational insights. The team can find a middle ground that satisfies everyone’s needs by identifying strategic objectives for the C-suite and practical, implementable solutions for maintenance managers.

In conclusion

Fluke Reliability’s survey indicated that C-suite executives and maintenance managers may be misaligned on how best to integrate AI and maintenance strategies. However, when respondents were asked how beneficial they anticipate AI to be in facing current and future industry challenges, not a single respondent answered “not beneficial at all.” 

AI adoption and integration are key strategies for meeting organizational goals. The manufacturers that stand to gain the most from AI are those that bridge the gap between executive strategy and maintenance operations. By aligning leadership goals with the needs of maintenance teams, organizations can fully leverage AI’s potential for improved decision-making and reliability.