One-Sentence Takeaway

Use AI to improve everyday work and reclaim time for solving problems, making decisions, and imagining better ways to serve customers, while keeping expert judgment in charge.

Summary

Dan's AutoCAD story made technology assistance concrete: copying precise parking-lot lines changed a repetitive task while the architect still directed the work. He connected that experience to the tools that followed, including spreadsheets, the internet, mobile, cloud, and AI. The leadership opportunity is to recognize where assistance can improve quality and reduce effort, then help teams put it to work.

The sentence-completion experiment, glue-in-pizza example, and familiar phone autocomplete illustrated why useful output still needs judgment. A plausible suggestion may miss the situation that matters to you. Your team's experience, priorities, and aspirations belong in the conversation. For INX, that means exploring formulation, connected enterprise information, and customer-value opportunities while respecting proprietary data and specialist responsibility.

The keynote moved from those business possibilities to immediate practices: ask AI to critique your work, reduce communication overhead, and try formats that make important ideas easier to remember and share. The work pyramid connected those practices to a larger purpose. Recovering time from communication, process, and investigation creates capacity for the problems, decisions, and future improvements that need leadership attention.

Action Items

[ ] Ask an approved AI tool how your role's work could change. Include the service you provide, outcomes you need, and constraints such as regulation, supply, systems, and adoption. Revisit the question monthly and challenge the proposed answers.

[ ] Try the performance-coach loop on one presentation, strategy draft, or other work product. Provide permitted prior examples, ask how the new work compares, and request specific changes that would make it one of your best. Apply the useful feedback.

[ ] Choose one recurring communication task for AI assistance, such as summarizing a permitted meeting or drafting a brief. Review the result and identify where the recovered time could improve problem solving or decisions.

[ ] Explore one INX opportunity below with the colleagues who own the work. Discuss what information it requires, what the AI proposal gets wrong, and which judgments must stay with the responsible experts.

[ ] Before sharing work or recording a conversation with a tool, confirm that the use fits your organization's privacy requirements. Treat AI output as material to evaluate before using it in decisions or communications.

Key Ideas

Assistance changes the task

The AutoCAD lesson is to look closely at the work a tool can help with. Removing repetitive effort can give an expert more room to contribute.

Useful output still needs judgment

Remember “glue in your pizza.” Check whether a suggestion makes sense for the task, the available evidence, and the context your team knows.

AI can be a coach

Drafting is one use. Comparing your work, explaining weaknesses, and suggesting improvements can also help you develop your own capabilities.

A proposed future starts a conversation

Ask for possibilities, turn them into a day-in-the-life story, and correct that picture with domain expertise. You retain responsibility for which ideas deserve attention.

Recover time for higher-value work

Communication, process, and investigation remain necessary. Improving them creates more room to solve, decide, and imagine.

Ink & coatings leader & team opportunities

The keynote explored these nine possibilities across three shifts. Use them as prompts for discussion about your workflows. Their usefulness depends on the information available, the tools, and the safeguards required. Proposed formulas, rule checks, forecasts, and customer conclusions still need the relevant experts' review.

From reactive formulation to predictive innovation

• AI formula predictions could draw on substrate, press, and safety data.

• AI rule checks could help formulators examine proposed material substitutions.

• AI supply forecasts could help teams consider reformulation earlier.

From disconnected systems to aligned execution

• AI could synthesize signals across SAP, CRM, laboratory, and manufacturing information.

• AI query assistants could help leaders find the enterprise information they need.

• AI drafted briefs could help translate strategy for cross-functional stakeholders.

From invisible service to proven customer value

• AI could help reveal costs across customers, services, and locations.

• AI summaries of service records could help sales teams explain the value delivered.

• AI analysis of account service patterns could help teams anticipate customer needs.

Talk Flow

1. Tools change how work gets done

• AI video introduction

  • Repeating a real task as tools develop can reveal changes in the quality of assistance available.

• The parking-lot story

  • AutoCAD made precise repetition faster; the architect still supplied direction and judgment.

  • Fear about jobs can obscure a practical opportunity to improve the work.

• The technology staircase & AI pinata

  • Familiar tools became ordinary ways of working through use.

  • Leaders should identify applications that create customer and team value.

2. Understand uncertainty & bring your judgment

• The sentence-completion experiment

  • Predicting a familiar next word offered an accessible introduction to generated output.

  • The audience's differing next answers showed why plausible continuation does not guarantee the answer you need.

• Confidence & imperfect answers

  • Decide how much confidence a task requires before acting on a suggestion.

  • Keep learning to use assistance while checking its results.

• Glue in pizza & phone autocomplete

  • Source material can contain jokes, bad advice, and missing context.

  • Accept suggestions that help and reject those that do not fit your intent.

• Memories & hopes

  • Your experience and aspirations shape how you judge a proposed action.

  • Different perspectives make the leadership conversation valuable.

3. Explore how Ink & Coatings work could change

• The industry question

  • Name the role, service, outcomes, and constraints to make the conversation relevant.

  • Refine the question around the work you are trying to improve.

• The nine opportunities

  • Explore formulation, connected information, and customer value together.

  • Proprietary information and specialist accountability shape what is appropriate to try.

• From a list to a future workday

  • A story or graphic can make an unfamiliar workflow easier to discuss.

  • Use your expertise to identify what the proposed picture gets wrong.

4. Build capability & reconsider where time goes

• Everyday assistance

  • Writing, research, images, inbox management, planning, and translation offer places to explore within approved tools.

• The performance-coach loop

  • Give AI your work and relevant prior examples, then ask for comparison and actionable critique.

  • Use the feedback to improve your next attempt.

• The work pyramid

  • Look at time spent communicating, following processes, and investigating issues.

  • Reduce some of that effort to create capacity for solving problems, deciding, and imagining improvements.

5. Improve communication & use the time recovered

• Meeting capture & support

  • Shared notes can help make expertise discussed in meetings easier to retrieve later.

  • Recording and tool use must fit the organization's requirements.

• Notes turned into a song

  • Experiment with formats people may revisit and share when a message deserves repetition.

• Translation demonstration

  • Language assistance can help colleagues and customers participate in a language comfortable for them.

  • Evaluate the tool and its privacy fit before using it for your work.

Closing Message - Managing in the world of more

Information, systems, expectations, and possible work keep growing while available hours remain fixed. The closing challenge was to flip the work pyramid and reinvest saved capacity in solving, deciding, and imagining the future of design, make, and engineering.