From Automation to Agents: Why Weak Data Makes AI Guess episode artwork

EPISODE · Dec 11, 2025 · 26 MIN

From Automation to Agents: Why Weak Data Makes AI Guess

from Everyday AI Podcast – An AI and ChatGPT Podcast · host Everyday AI

Algorithms and automations have been buds for a decade plus. 🤝But the old 'smart' automations were rigid. If one thing was wrong, the automation would bust. But with LLM-powered agents? Those automations are different. If something's wrong, the agent might just..... guess. 😳Weak data = weaker outcomes. Here's how to fix it when agents come first and they're gonna finish the job, whether the data is strong or not. From Automation to Agents: Why Weak Data Makes AI Guess -- An Everyday AI chat with Jordan Wilson and Ed MacoskyNewsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageJoin the discussion:Thoughts on this? Join the convo and connect with other AI leaders on LinkedIn.Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: [email protected] with Jordan on LinkedInTopics Covered in This Episode:Automation vs. Agentic Workflows: Key DifferencesAI Agents: Data Quality and Output RisksAgentification Trends in Enterprise AutomationPros and Cons: Converting Automations to AgentsAI Agents Impact on Business ProcessesImportance of Data Governance in AI AgentsAI Agent Control Towers and ObservabilityMeasuring ROI: AI Agents and Data InvestmentsTimestamps:00:00 "Trusting AI for Business Growth"06:31 "Agent-Based Automation: Pros & Cons"08:29 "AI Agents Simplify Workflow Management"10:40 Expense Report Workflow Frustrations15:05 AI Governance and Data Integrity19:04 "Governance and Multi-Agent Data Strategy"22:50 "AI ROI and Data Focus"26:01 AI Studio: Create Apps FasterKeywords:AI agents, Agentification, Agentic workflows, Automation, AI-powered automation, Business process automation, Deterministic workflows, Non-deterministic workflows, Data quality, Data governance, Data management, Integration platforms, Boomi, Chief Product and Technology Officer, Large language models, Generative AI, Rigid workflows, Flexible workflows, Conversational agents, Expense report automation, Policy adaptation, AI decision-making, Human-in-the-loop, AI observability, AI traceability, Multi-agent orchestration, Ecosystem synchronization, Agent control tower, AI governance tools,Send Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info)

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Algorithms and automations have been buds for a decade plus. 🤝 But the old 'smart' automations were rigid. If one thing was wrong, the automation would bust. But with LLM-powered agents? Those automations are different. If something's wrong, the agent might just..... guess. 😳 Weak data = weaker outcomes. Here's how to fix it when agents come first and they're gonna finish the job, whether the data is strong or not. From Automation to Agents: Why Weak Data Makes AI Guess...

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From Automation to Agents: Why Weak Data Makes AI Guess

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