Greg Moser’s Post

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Strategy Advisor, Mentor, Company builder, CEO/COO

Focusing a lot of effort on Gen AI is a waste of time for 99% of companies. Cut your AI expectations in half. However here are 3 practical areas in tech/AI you SHOULD be running towards: 1. Clean your room before you go play! Your mum was right…... before you chase after “new toys”, make sure your company has good hygiene. There are tangible top and bottom line impacts by investing in Workflow and Collaboration tools (some with AI). They’re easy to integrate and bring transparency for multifunctional teams and your clients.   2. Does everyone know the score? It’s not sexy to invest in good data structure..... Most people don’t know what data scientists do..... and BI dashboards seem like magic boxes.  However, good, transparent data, with intelligent insights UNLOCKS your team’s abilities and allows less people to manage more. Ask yourself: Do you still brief from slides   or   do you brief from almost-real time dashboards? 3. Don’t let them rob the store! A great product with even tiny security flaws is useless when it gets hacked. I know firewalls, EDRs, encryption protocols, DoS attacks feels like IT claiming “the sky is falling.” (and needing more $$).  However, there are some really reliable, practical AI integrations with security now that keep IT headcount flat and make service faster while still providing reliable security at scale. You need to invest in security as you grow.... ***Note IT professionals: you need to be more transparent and use plain english when talking to other functional leaders. ss     The reality is there are some practical Ai integrations that work today, but I believe industries with “no-fail” requirements should first look at practical technology that can make an impact today's results…. After that you can go play with some shiny new toys.

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Fatemeh (Setareh) ShiraziZand

Moracle Limited - Accounting Solutions for Your Business | Business Development Specialist at Moracle Limited

1mo

Great points! Focusing on foundational hygiene, data transparency, and security is crucial before chasing shiny new AI tools. Practical investments in these areas deliver real, immediate impact—everything else is a bonus!

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