Why AI Tools Still Can't Match a Basic Human Assistant

Despite promises of revolutionary intelligence, today's AI applications consistently fail at tasks that would embarrass any competent human assistant. While companies like OpenAI push to collect virtually all enterprise data, their existing tools struggle with basic contextual awareness.

The gap between AI marketing promises and real-world performance is stark. Tech journalist Evan Schuman highlights everyday examples that expose how "smart" systems consistently miss obvious context clues that humans would never overlook.

Real-World AI Failures That Prove the Point

Smart Home Devices That Aren't Smart:

• Amazon Ring doorbells alert users about spiders walking across cameras despite being set to "human detection only"
• The same systems trigger false alarms for rain, sunsets, and other non-human activities

Smartphone "Intelligence" That Lacks Context:

• iPhones remind users about meetings while they're actively driving to those same meetings using Apple Maps
• Devices repeatedly send identical notifications from different news sources about the same election results
• Apple Watches programmed to show time and calendar instead display random weather reports or media controls

The Core Problem: Missing Contextual Intelligence

These failures reveal a fundamental flaw in current AI systems. Despite having access to rich data sources—location, calendar entries, user behavior patterns—these tools fail to synthesize information intelligently. A human assistant would never interrupt a meeting drive to remind about the destination or send repetitive updates about the same news story.

What This Means for Enterprise AI Adoption

The implications extend far beyond consumer inconvenience. If AI systems can't handle simple contextual decisions with readily available data, how can businesses trust them with sensitive enterprise information? Companies should evaluate whether AI vendors can effectively use existing data before sharing additional sensitive business intelligence.

🔗 Read the full article on Computerworld