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The Most Valuable Data is Homegrown

Throughout these early days of Generative AI attention has naturally concentrated on its visual outputs. AI videos and images have dominated the public perception of what AI can do. Within businesses the capabilities of being able to draft written material and being able to out-Google Google are to the fore amongst popular useages.

Yet the reality for many businesses will be the capability of being able to upload business data and farm enterprise data and then for GenAI to work with you on your own data that is of greatest value. The first experience of being able to talk to your own data - quite literally when using voice mode - seems almost surreal.

Zero understanding is a great starting place because you can ask GenAI and it will talk you through what you might like to get from the data. Or if you know what you want just ask and GenAI will deliver and suggest some further, often very useful, ideas of what can be extracted.

If you already know something, or a lot, about the data GenAI becomes a fantastically easy and quick database/spreadsheet utility. For farmers, using GenAI is the easiest way of understanding and making decisions from both farm financial data and enterprise records/production.

  • Run what-if and scenario models (price rises, yield changes, interest-rate shifts)
  • Produce rolling forecasts and budget vs. actual variance reports
  • Calculate cohort metrics (e.g., monthly customer retention, repeat purchase rates)
  • Create instant KPI dashboards with charts pulled from uploaded sheets
  • Merge multiple sheets (or files) and match on keys to create a single, tidy dataset
  • Build quick pivot analyses and ranked leaderboards (top customers, slowest SKUs, etc.)
  • Detect outliers, broken formulae, missing values and duplicate rows
  • Standardise units and categories (kg vs. tonnes, product names, cost centres)
  • Reconcile lists (stock on hand vs. sales ledger) and flag mismatches
  • Generate tailored reports per field/cow/enterprise/client etc.
  • Enrich rows by joining to look-up tables you provide
  • Compute reorder points and basic demand forecasts from historical purchases/sales
  • Identify payment risks (late payers, average days to pay) from AR spreadsheets
  • Build cleaned contact lists (dedupe, split names, validate e-mails)
  • Turn timesheets/rotas into labour-cost summaries and utilisation metrics
  • Convert ad-hoc data dumps into a consistent template ready for your systems
  • Combine spreadsheets, PDFs and images into one place for quick analysis and summaries
  • Extract key fields (names, dates, prices) from invoices, forms and receipts
  • Clean and standardise messy data (deduplicate, fix formats, flag gaps)
  • Turn uploaded reports into briefings, slide outlines or FAQs
  • Classify and tag documents so they’re searchable by topic or client
  • Reconcile records (e.g., orders vs. deliveries) and spot mismatches
  • Generate charts and plain-English insights from uploaded datasets

    • In the future, because of its fantastic simplicity of use, GenAI will become the standard way of working with data. And currently being built by the AI platforms is the seamless integration of full intra-platform database functionalities where your GenAI is also a database in its own right.