Trust, tools and turning points Yet for all the promise, there remains a broad spectrum of attitudes toward AI across our industry. Some are already piloting tools and building in-house expertise. Others remain cautious - unconvinced of reliability, ethical alignment, or strategic fit.


This is understandable. AI is complex. It raises serious questions about data governance, intellectual property, security, and organisational readiness. For many, it still feels intangible or too far removed from daily operations.


But here’s the reality: the tools are already arriving. AI is being integrated into ERP systems, laboratory tools, CRM platforms, and quality control software. Even without “building AI,” companies are starting to use it - often without knowing.


What’s needed now is not just more tech, but more intent.


Intent to experiment. Intent to learn. Intent to lead responsibly.


From automation to augmentation One of the most important mindset shifts is to stop thinking of AI solely in terms of automation - doing the same thing, faster and cheaper - and start thinking in terms of augmentation.


As noted in my recent UKLA conference presentation, generative AI is about more than productivity gains. It unlocks new dimensions of creativity, insight, and problem-solving. And now, with the rise of agentic AI, we are moving into systems that can reason, plan, and act - with increasing levels of autonomy.


This shift presents new opportunities across technical and commercial functions: • In R&D, AI can generate and evaluate thousands of molecular structures in seconds.


• In customer support, agents can interact with service histories and technical bulletins to generate tailored recommendations.


• In operations, workflows can be designed to run adaptively with minimal human intervention - and maximum traceability.


But none of this replaces the role of human


professionals. On the contrary, it makes their expertise even more vital. AI is not an excuse to reduce human input. It is an invitation to amplify it - through critical thinking, ethical judgment, and domain-specific insight.


Integrity is not optional


As the technology advances, the conversation around ethics, bias, transparency, and unintended consequences becomes even more pressing. From responsible data handling to explainable outputs, the lubricants industry, like all sectors, must ensure that innovation does not come at the cost of integrity.


Some of the key guardrails to consider: • Data privacy and protection, especially for customer, formulation, and supply chain data.


• Transparent use policies, so employees understand how and when AI is being applied.


• Bias mitigation, to ensure outputs are fair and reflective of diverse data inputs.


• Oversight mechanisms, to validate AI-generated recommendations before implementation.


• Clear accountability, so responsibility does not become diffused between systems and people.


Ethical leadership is not just about compliance. It’s about earning and sustaining trust; from employees, customers, regulators, and the public. It starts with clear intent and open dialogue.


Building capability at every level If AI is to become a real capability, not just a buzzword, then it must be embedded in organisational culture. That means moving beyond isolated experiments to widespread literacy and strategic alignment.


This is not solely a technology function. It is a whole-business effort. From the boardroom to the lab bench, from supply chain managers to sales teams, AI understanding must be cultivated, not assumed.


Key steps to consider: • Upskilling and education - formal and informal training to build baseline knowledge.


• Pilot projects - low-risk experiments that demonstrate value and build confidence.


• Cross-functional collaboration - tech and business teams working together to design meaningful applications.


LUBE MAGAZINE AR TIFICIAL INTELLIGENCE DECEMBER 2025 23


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