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Texas voters had a smooth Nov. 3 while county staff worked around a slow state registration system.
Now they're helping fix it.
Election software should be built with its users. It's how we built our state-certified ePollbook.
https://t.co/xQUmtOIjtc
#GovTech#ContentActive
Most AI conversations start with the tool; ours start with you.
Our free AI Readiness Score rates you on strategy, data, infrastructure, workflows, talent and governance. Notice how few are about the AI itself.
3 minutes: https://t.co/p0iLOTSfPI
#AIReadiness#ContentActive
71% of tech leaders call their infrastructure modernized. Two-thirds of CIOs say their foundations need major work before AI can scale.
21% scrapped a major AI project after it failed. (Kyndryl)
Fix the foundation first:
https://t.co/xQUmtOIjtc
#AIStrategy#ContentActive
Healix runs infusion centers for 200+ physician practices and hospitals.
Coordination lived in email and spreadsheets.
We rebuilt their provider portal and mobile app with real-time data and automated reports.
Case study: https://t.co/hknf2cKn6j
#HealthTech#ContentActive
When everything is a top priority, nothing is.
CMU's CERT Division narrowed cyber research to 7 areas.
This stood out: keeping legacy industrial systems secure as they get connected.
https://t.co/xQUmtOIjtc
https://t.co/US6JFAhELH
#CyberSecurity#SecureByDesign
80% of CEOs say their job is at risk if AI doesn't deliver results by the end of 2026.
That pressure is why every AI project plan needs one thing: how to shut it off.
https://t.co/lz8ioL20SC
Benchmark your AI governance in 3 min:
https://t.co/p0iLOTSfPI
#AIGovernance#CIO
"Technology in a large organization is already a wild animal. With AI, the risk is that it breaks free." Ben Reason, Livework
Adding AI to an unmapped workflow is how it gets loose.
Check your AI governance in 3 min:
https://t.co/p0iLOTSfPI
#AIGovernance#ContentActive
Cimarron Energy's field IoT devices were reporting, but the data sat in separate systems.
We moved it into one Azure data warehouse and built real-time Grafana dashboards with alerts for their customers.
Case study: https://t.co/o7SbX2Rvdc
#IoT#EnergyTech#ContentActive
Hosting AI in-country doesn't mean you control it.
A closed model means the vendor owns the training data and can end your license. Real control is holding your own keys and audit trail.
Check your foundation:
https://t.co/p0iLOTSfPI
#AIGovernance#AI#EnterpriseSoftware
The best fire alarm test is the one you don't hear.
Siemens' new Acend Intelligent lets teams check every device remotely without sounding an alarm.
The bigger story: safety hardware is now a software problem.
https://t.co/xQUmtOIjtc
#IoT#SoftwareEngineering#ContentActive
Field technicians spend hours manually setting up MAC addresses & Wi-Fi keys on factory floors.
New zero-touch standards prove that true scale requires removing manual setup friction.
Full piece: https://t.co/Y3H8IDrEFV
#IoT#WorkflowAutomation#ContentActive
35% of AI-generated code hits production before developers understand what it does.
Teams spend 17 hrs/week debugging AI mistakes. AI writes code fast, but it doesn't design enterprise systems.
https://t.co/pgpDppVhVY
#TechLeadership#SoftwareEngineering#ContentActive
A welding issue on one line. A vendor issue on another. Logged separately, by different people, on paper.
Each one visible. Their combined effect on the delivery date, invisible until after the job closed.
Most operational data problems look like this.
https://t.co/5EOXDU8yK3
Botha is writing about startups. The failure mode is identical in enterprise, where building the wrong thing costs quarters instead of weekends.
https://t.co/ZetFFB5arZ
Speed stopped being a competitive advantage the moment AI made everyone fast.
Anina Botha argues the real differentiator is value realization: when a customer actually experiences the benefit they were promised.
Product-market fit proves demand exists.
AI accelerates the build. It does not decide what should be built.
Define the workflow. Map the data. Find where value lands for the person doing the work. Then build.
In that order speed compounds. Reversed, you get systems that demo well and go unused.
Massachusetts is tackling extreme heat, and their first step is building data infrastructure to connect siloed state and local agencies.
You can't solve systemic problems with siloed data.
Audit your data infrastructure:
https://t.co/p0iLOTSfPI
#GovTech#DataSilos#Resilience