Only 37% of manufacturers are prepared for the implementation of AI, according to a study.

While 87% of industrial executives and technical specialists report that the ROI of their AIOps initiatives has met or exceeded their expectations, only 37% say they are fully ready to implement AI at scale. With 62% of AI projects still in the pilot or development phase, and 90% of respondents agreeing that improving data quality is critical to AI success, the findings highlight an industry eager to leverage AI to streamline operations, reduce costs, and navigate increasingly complex global supply chains, but still struggling to bridge the gap between its ambitions and large-scale enterprise-wide AI implementation.*

As manufacturing companies strive to advance their AI transition, several significant obstacles hinder widespread adoption. While more than half (57%) of industrial companies express confidence in their AI projects, and the vast majority agree that improving data quality is critical to their success, persistent data quality challenges remain a major hurdle. Nearly half (47%) are not convinced their company's data is accurate and complete enough to deliver the desired results, and only 34% rate their data as excellent in terms of relevance and suitability. These discrepancies highlight a clear disconnect between executive optimism and the technical realities of implementation.

For Richard Tworek, Chief Technology Officer at Riverbed: “The industrial sector is investing heavily in AI to transform its IT operations, and our survey results show that nearly nine out of ten companies in this sector (87%) are already meeting or exceeding their ROI expectations for their AIOps investments. However, many still face significant challenges, including gaps in preparedness and responsiveness, as well as data quality issues that are hindering progress. As a data-driven company, we help our manufacturing customers bridge these gaps with safe, secure, and accurate AI, grounded in high-quality, real-world data. We deliver practical, AI-powered solutions that enable organizations to deploy AI enterprise-wide.”

Consolidating tools: a major IT priority for manufacturers

Faced with evolving processes and shifting priorities, manufacturers have sought a range of IT tools to support their constantly changing objectives. The study revealed that, on average, companies in this sector currently use 13 observability tools from nine different vendors. In response, 95% of manufacturers are consolidating their tools to reduce proliferation, aiming to lower costs, streamline operations, and optimize IT efficiency. Vendors would be wise to continue exploring the capabilities of their tools, as 91% of manufacturing companies are considering new tools as part of their consolidation efforts. The key capabilities and motivations that manufacturing executives are actively considering when consolidating tools are improved tool integration and interoperability (48%), reduced vendor management overhead (47%), and improved IT productivity (46%).

Unified communications needs to be reformed

As AI and remote working are poised to transform manufacturing companies worldwide, the survey revealed an enthusiasm for unified communications tools and their integration into operations.

• The study revealed that 42% of employees use unified communication tools throughout their work week and 66% of respondents in the manufacturing sector say these tools are essential for working efficiently on a daily basis.
• Despite their increasing adoption, these tools can still be significantly improved. Less than half (45%) of respondents are satisfied with the performance of unified communications tools, and 42% of manufacturers report encountering problems with video calls, messaging platforms, etc.
• The three main challenges that companies face with unified communications tools are limited visibility (51%), dropped calls (42%), and difficulties integrating with other enterprise systems (38%).

Adoption of OpenTelemetry in the manufacturing sector

The industry leaders surveyed also shared their views on OpenTelemetry (OTel) and its role within their organizations. The study revealed that 44% have fully implemented OTel, while 42% have adopted it. Overall, 97% agree that OpenTelemetry's cross-domain correlation is essential to their observability strategy. The vast majority (93%) state that OTel forms the basis for future initiatives such as AI-driven automation, and 37% indicate that OTel is already mandatory in their organizations, demonstrating significant interest in this technology.

AI data movement and network performance

With data already identified as a key success factor in AI initiatives, 91% of industry respondents cited data transfer and sharing as important to their organization's overall AI strategy, with 31% stating that it is essential and fundamental to AI design and implementation. To further support AI initiatives, 75% of manufacturing respondents plan to implement an AI data storage strategy by 2028.

Respondents also confirmed that the three main factors to consider in order to enable their organization to move and process data effectively were:

• Network performance and capacity (96%)
• Cost of data transfer and storage (94%)
• Proximity of the AI ​​model to the data and interoperability between environments (93% in both cases)

Moreover, as manufacturing companies strive to remain competitive, ensuring superior network efficiency and robust data security is a top priority, as 79% of them state that network performance and security are critical to their AI strategy.

To learn more about how organizations are addressing their gaps and managing the adoption and implementation of AI, see the full report at this address.

Methodology :

Riverbed's global survey on the future of IT operations in the age of AI polled 1.200 business decision-makers, IT leaders, and technical specialists across seven countries and multiple sectors, including manufacturing. The study was conducted by Coleman Parkes Research in July 2025.

* Note: Unless otherwise stated, all data and percentages mentioned in the press release are percentages calculated from responses to the global Riverbed 2025 survey: The Future of IT Operations in the AI ​​Era. Respondents included business leaders, IT managers, and technical specialists from seven countries working in the manufacturing sector.

Image illustrating the article via Depositphotos.com.