What barriers have you faced in implementing AI? (Select all that apply)


For some, AI signals competitive advantage and innovation. For others, it raises alarms about job displacement, intellectual property, and governance.


• Early adoption vs. wait-and-see


How would you describe the impact of AI on your operations so far?


Efficiency gains and faster decision-making dominate perceived benefits. Respondents cite improved resource utilisation, better customer insights, and enhanced product development.


But barriers loom large. The top of these is the lack of skilled staff (26%), followed by high implementation costs (23%), and cybersecurity concerns (20%). These echo broader debates about AI’s applicability beyond administrative or marketing functions.


• Trust vs. scepticism


A minority are pushing ahead with implementation, but most remain cautious, waiting for clearer ROI and more robust solutions.


Current and future applications of AI


Overall, AI adoption is not too bad in the lubricants industry compared to other industrial based industries.


The majority of respondents stated that most early AI applications are confined to commercial functions such as sales and marketing analytics, customer engagement tools, and chatbots that can improve customer experience through personalised engagement.


Concerns about data quality and reliability persist. Over 15% of respondents question whether AI outputs can be trusted, fearing over-reliance on technology and poor or incompatible data.


• Disruption vs. Risk


How has AI improved your business? (Select all that apply)


Operational applications, such as predictive maintenance, logistics optimisation, and quality control were also cited as areas of actual or potential suitability for AI-driven technology.


However, technical domains, including laboratory automation and research and development activities, were mentioned by only a minority of respondents as being currently for AI application. AI’s technology is seen as not yet being ready to tackle these challenges.


Looking ahead, as the level of AI technology matures, respondents expect AI software to interact with manufacturing hardware, enabling advanced analytics and forecasting while driving end-to-end process automation across supply chains. This is a longer-term application, and specific timeframes are hard to pin down.


6 LUBE MAGAZINE AR TIFICIAL INTELLIGENCE DECEMBER 2025


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