SOURCE: Kay Sever | May 29, 2026
In the first five months of 2026, I have shared what I have learned about AI capabilities (which change continually), AI components, AI metrics, and the complexities of linking AI to existing IT systems. I have also discussed corporate risks that I recognized that are not discussed by AI developers (accuracy, depth of knowledge, resources needed, AI integration timelines, what data to share and how to protect its confidentiality, etc.)
Starting this month, we are going to explore AI integration options that executive teams, senior leadership teams and mine/plant management teams will be considering as they strategically adopt the use of AI into functional groups across the company. The decisions these teams make will affect departments that report to them, as well as customer/supplier departments that are upstream and downstream in the organization. This month we will start with high level integration issues that will help define the implementation scope to focus on.
Where to Begin
The GOOD NEWS for every management team is this: AI is unique because it comes with an open-ended list of implementation options that are customizable for each company, which means executive teams will have control of where they employ AI organizationally and what they want AI to do for them and their people!
Making a list of questions can help a team hone in on the most important areas to include in the scope. Because of my long-time specialization in performance optimization, I think about “what’s missing” when I think about improving anything because missing data/information are often the key to capturing hidden upside potential or FINALLY solving a recurring problem. With that perspective in mind, here are some questions that will help your team define an AI scope for your company.
What part of the organization could benefit most from AI data/analysis?
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- Production Value Stream – by department, follows product flow
- Production Value Stream – by department, vertical integration per org chart
- Support Functions – by department, follows information flow
- Support Functions – by department, vertical integration per org chart
- Management System – decision tools, communications, execution
- Management System – problem solving, teamwork, collaboration
When answering these questions, think about things that are hard to do in your organization.
What kind of production data are currently captured for your equipment?
What kind of production data or support function data are NOT captured by your current systems? The answer to this question is important because data NOT captured is a limiting factor on the kinds of analyses AI can perform.
Is there production data for a department/function that is needed upstream or downstream to meet internal or external customer requirements?
Have you identified weaknesses/voids in your management system that put your supervisors and superintendents at a disadvantage? Could AI be used to strengthen the quality of information used day to day by your team?
Have you had capital projects that never delivered the expected/promised ROI? Depending on the root cause of the shortfalls, AI may be a tool to help prevent this from happening in the future.
Have you unintentionally budgeted for production goals that were not achievable (i.e., they were higher or lower than the min/max limits of your equipment/processes)? When this happens, trust between management and the workforce AND management’s credibility with the board are at risk. Maybe AI could be employed before budgets are finalized to help prevent this from happening in the future.
Are support groups lacking in tools to best serve the production value stream? AI may be able to help strengthen the support your production people need.
This is not a complete list of AI scope questions; however, this list does provide a starting point for executive teams as they hone in on the best initial AI scope for their companies (at least for Phase One). These questions can also help prioritize and group potential AI applications for future implementation phases.
Next month: More on AI implementations and factors to consider.
Kay Sever is an Expert on Achieving “Best Possible” Results. Kay helps executive and management teams tap their hidden profit potential and reach their optimization goals. Kay has developed a LIVESTREAMmanagement training/coaching system for Optimization Management called MiningOpportunity – NO TRAVEL REQUIRED. See MiningOpportunity.comfor her contact information and training information.
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- About Us
Kay has worked side by side with corporate and production sites in a management/leadership/consulting role for 35+ years. She helps management teams improve performance, profit, culture and change, but does it in a way that connects people and the corporate culture to their hidden potential. Kay helps companies move “beyond improvement” to a state of “sustained optimization”. With her guidance and the MiningOpportunity system, management teams can measure the losses caused by weaknesses in their current culture, shift to a Loss Reduction Culture to reduce the losses, and “manage” the gains from the new culture as a second income stream.
