Beyond the Hype: Part 2. Productivity, Not Parlour Tricks
Why useful AI depends on repeatable workflows and business outputs, not one-off demonstrations.
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AI in Practice
Explore practical AI applications for everyday work, from identifying useful opportunities to evaluating results and repeatable workflows.
AI can support drafting, research, analysis, reporting and business processes. But the most impressive demonstration is not necessarily the most useful application. The opportunity lies in understanding where AI can help with meaningful work.
Understanding the Topic
From impressive demonstrations to useful work
Generative AI can produce convincing results in seconds, but organisations need to look beyond what a tool can demonstrate.
A useful application starts with a real task or problem: what is someone trying to achieve, what information is needed, and what would a better outcome look like?
Sometimes a simple AI-assisted task is enough. Other opportunities involve repeatable workflows. In either case, people must understand limitations, review outputs and remain accountable. The objective is not to use AI everywhere.
AI in Practice
Where AI can help
Everyday Tasks
Drafting, summarising, research, analysis and communication, with appropriate review.
Business Workflows
Reporting, customer feedback and repeatable processes, grounded in reliable information.
Decision-Making & Problem-Solving
Exploring options and analysing information without treating AI outputs as verified facts or replacing professional judgement.
Workplace Examples
What could AI help with?
These are illustrative possibilities, not completed client projects or measured outcomes. Human checking and approved information-handling practices remain essential.
Customer feedback
AI contribution: Group recurring themes across feedback.
Human responsibility: Check findings against the original comments.
Meeting preparation
AI contribution: Summarise relevant background documents.
Human responsibility: Verify accuracy, omissions and relevance.
Document drafting
AI contribution: Prepare an initial draft of a report or communication.
Human responsibility: Check facts, suitability, tone and confidentiality.
Operational reporting
AI contribution: Help identify and explain patterns in supplied data.
Human responsibility: Validate calculations and investigate anomalies.
Getting Started
Start with the work, not the tool
Look at tasks, information, decisions and existing processes before choosing technology. Consider how often the task occurs, what information it requires, how results will be checked and whether AI assistance would produce a worthwhile improvement. Start with manageable applications that help people test assumptions, learn and build confidence.
Further Reading
Explore the articles
Explore Further
Related topics
AI Adoption & Capability
Building the skills, confidence and judgement people need to use AI effectively.
AI Safety, Security & Governance
Understanding AI risks and making informed decisions about responsible use.
Common Questions
Frequently asked questions
Examples include drafting and revising routine communications, summarising material for review, organising notes, preparing first-pass outlines and exploring options. Each use still needs appropriate information handling and human checking.
Start with recurring tasks that consume time or create friction. Describe the desired outcome, required information and existing checks before selecting a tool. Prioritise manageable work where results can be reviewed.
Tasks involving language, drafting, summarisation or exploratory analysis may be good candidates when errors are detectable and information can be used safely. High-stakes decisions and sensitive workflows require stronger controls and may not be suitable.
Compare the current process with a small trial. Assess output quality, time saved, staff effort, privacy and security risks, review requirements and whether the improvement is repeatable. A convincing demonstration is not sufficient evidence of value.
Use deterministic automation when the rules are clear and consistent outputs are essential. Generative AI can help with less structured language tasks, but its variability means additional review and safeguards may be necessary.
Training & Enablement
Build practical AI capability
Useful AI adoption starts with understanding the work people do. We help teams identify appropriate opportunities, build practical AI skills and develop the judgement needed to use AI effectively in everyday tasks and workflows.