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The ChatGPT Trap: Why Enterprise AI Projects Fail
SAP Architect Reveals Critical Enterprise AI Implementation Mistakes | 6,200% Growth in AI Presentation Tools | Ex-OpenAI Leader Secures $2B for Superintelligence

Welcome to Homebase AI - A weekly newsletter where we share our interviews with founders & leaders building next-gen AI companies and curate interesting news, insights & trends in the AI space for our community members.
Whatβs on tap today:
Our interview with Benjamin Smokovich
Weekly Headline Recap
What's trending in AI this week
Community Update
How Homebase Helps You
AI Founder Story
Avoiding "The ChatGPT Trap": Enterprise AI Lessons
Quick Background
Benjamin Smokovich serves as a Global Business Architect at SAP, where he's working on an internal AI project across the entire sales organization with 40 different use cases. As he explains, "business architecture is one of the most important roles in a organization, whether it be startup or large enterprise. It is the Steve Jobs of any organization, right? You have to be a visionary. You have to understand what the needs are of the organization and you have to bring that to life with your vision."
In our latest episode, he shared critical insights on what he calls "The ChatGPT Trap" - a phenomenon where large enterprises rush to implement AI solutions with little strategic direction, resulting in underwhelming results and disappointed customers.
Key Achievements & Insights:
Large enterprises are falling into "The ChatGPT Trap" by pouring massive resources into AI without clear capitalization strategies
Many companies over-market their AI capabilities while delivering solutions that are merely "LLM wrappers" with no additional workflow value
The pitfall comes when "users get on that solution and they come to find out that it's not what it was advertised to do"
Companies thought they could "lay off massive people and replace people with AI" but ended up having to "hire people back" when they realized their mistake
Benjamin describes his SAP initiative as trying to "go from iPod to iPhone" while avoiding the common traps of enterprise AI implementation
Knowledge workers are critical for successful AI implementation, as they understand the workflows that need to be embedded into systems
The successful enterprise AI approach: "take workflows, data, and match that with content, then wrap that in an LLM or an agent"
Watch the full interview below! π
The Ultimate Lesson
To avoid "The ChatGPT Trap," organizations must balance automation with innovation. Smokovich warns that companies rushing to implement AI without proper knowledge workers will fail to deliver meaningful value. Companies must "be clear about expectations" and focus on embedding real workflows and domain expertise into their AI implementations.
The future belongs to those who can leverage knowledge workers' expertise to create truly useful AI solutions. As our conversation revealed, AI can make mediocre employees great, but the real competitive advantage comes from making great employees exceptional through thoughtful AI implementation.
Read the full case study on "The ChatGPT Trap" to learn how your organization can avoid this common AI pitfall β
βRight now we need to just be clear about expectations. I think companies thought that they were going to be able to lay off massive people and replace people with AI. And they, I think they even jumped the gun. They did lay off people. And then they realized like, crap. I mean, we hear cases where they had to hire people back.β
HEADLINE ROUNDUP
Headline recap
Ex-OpenAI Leader Raises $2B for Safe Superintelligence Startup (Link) Ilya Sutskever's ambitious venture attracts massive funding to tackle AI safety challenges with unprecedented investor confidence.
Sam Altman Calls ChatGPT-Generated Story "Beautiful Trash" (Link) CEO's contradictory critique sparks debate about AI creativity and content quality as he praises yet dismisses AI-written fiction.
Microsoft Invests $298M in South Africa's AI Infrastructure (Link) Tech giant commits significant funding through 2027 to boost cloud and AI capabilities in rapidly growing African market.
OpenAI Donates $50M for AI Research at Harvard and Beyond (Link) Harvard joins 14 other institutions receiving substantial funding from OpenAI's NextGenAI initiative to advance artificial intelligence research.
China Launches 'Manus' AI Assistant Following DeepSeek Success (Link) New AI assistant emerges from China's growing tech sector as the country continues expanding its footprint in artificial intelligence development.
TRENDS
What's trending in AI
Presentations.ai
Key Player: Founded by former Canva executives Tom Gadsby and Daniel Riddell who launched the platform in 2023 after securing $5M in seed funding from Sequoia Capital.
Market Value: Currently valued at approximately $120M following their Series A round of $18M in late 2024, with projections suggesting a 2X valuation increase by 2026.
Adoption: Over 165,000 monthly active users with 6,200% growth in the past two years, primarily driven by enterprise customers in marketing, sales, and education sectors.
Recent Developments: Launched GPT-4-powered slide generation capabilities in January 2025, enabling users to create entire presentations from simple text prompts with built-in fact-checking.
Growth: Presentations.ai has disrupted the presentation software market by focusing exclusively on AI-first design principles. Their rapid customer acquisition stems from reducing presentation creation time by 78% compared to traditional tools, with enterprise subscriptions growing at 213% annually.
Why It Matters: The platform addresses a critical pain point in business communication as companies struggle with information overload. By automating design decisions and content suggestions, Presentations.ai allows users to focus on storytelling rather than technical details, democratizing high-quality presentation creation.
The Big Picture: Presentations.ai represents the next evolution in productivity software where AI doesn't just assist but becomes the primary creation engine. As one of the first successful vertical AI applications in the business presentation space, it signals a broader shift toward specialized AI tools replacing general-purpose software across the enterprise stack.

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