European TEDAI conference in Vienna · I ❤️ AI Community

European TEDAI conference in Vienna

Hi all,

coming from Vienna with some fresh inspiration and I thought I would share some of it. First, the best contributions, second, some AI business application learnings across the board from 2 days. I would be curious to hear your comments - here my LinkedIn post (https://tinyurl.com/jvyj3yuf):

Here are the details

1) My highlights as a business builder who is passionate about creating disruption with technology:

Des Traynor, co-founder of Intercom – Shared his $100M bet on AI, building a custom LLM with fin.ai that proactively “wiped out” Intercom’s traditional business model. Their AI agent resolves 65% of queries out-of-the-box (85% when optimized) with resolution-based pricing and even a success guarantee. The next horizon: evolving into a generalist agent that boosts revenue through contextual cross- and upselling.
Mercedes Bidart, CEO of quipu bank – Transforming access to credit for the 99% of LATAM businesses, who are micro businesses and represent ⅓ of the region’s GDP. AI analyzed non-traditional data such as text messages, social profiles, and business video pitches and converts neighborhood trust into a lending currency. This cuts credit access from years to months. Her message: “Being poor is not only expensive but can also be risky, let's use AI to fix it”
Hardy Pemhiwa, CEO of Cassava – Advocated that it is “Africa’s time for AI.” By 2050, 60% of the world’s youth will be in Africa. His vision: an AI factory enabling AI-powered community entrepreneurs. This will empower digital natives by creating employment and closing rural skills gaps (e.g., teachers, nurses, agronomists). The goal: build inclusive AI infrastructure, optimized for impact over clicks.
Diane L., AI filmmaker Afro Futcha – Leveraged diverse AI tools to create award-winning movies and music videos. Her session, held in a movie theatre, gave the right context to experience her innovative work and spark insightful discussion. For those curious about AI-made films, she recommends escape.ai.
Advait Sarkar, Researcher at Microsoft – Reminded us that AI can assist, speed up work, deliver better answers, and automate the known. But his research shows over-reliance reduces creativity, critical thinking, memory, and metacognition. He’s working on an app that makes AI a true tool for thought: helping users understand tasks more deeply, produce higher-quality work, ask sharper questions, and explore the unknown. This strengthens intentionality and upskills knowledge workers across all critical dimensions.

2) My AI business application learnings across the board from 2 days:

Leadership mindset – Similar to digital transformation, but harder: (1) employee fear, (2) speed & depth of change, (3) ethical & legal challenges. Leaders must address fear openly and stay technology-forward — even in functions like HR or Legal. Reverse mentoring (tech-savvy colleagues coaching executives) can accelerate this shift
Scaling beyond pilots – Many companies stall at PoC stage. Success depends on the right scaling partner and anticipating hidden costs (integration, monitoring, governance).
Hands-on leadership – Executives need to build or apply AI themselves to grasp the magnitude of change. Without this immersion, strategy risks becoming abstract.
Critical thinking – Delegating to AI does not replace judgment. Businesses must train people to probe, question, and validate AI output to avoid poor decisions.
Performance visibility – Embedding AI in workflows exposes underperformance and widens the gap to high performers. Expect shifts in how performance is measured and rewarded.
Redefining trust – In business relationships, assume AI is being used — but don’t assume the output reflects the sender’s own thinking. Attribution, transparency, and cultural sensitivity will become central to trust.
Adoption & pricing – For new AI solutions, success-based pricing and phased adoption (no “rip & replace”) de-risk implementation and build confidence.
Cultural lens – Trust in AI differs across markets. Beyond localization, leaders must ensure AI aligns with human standards and customs in each context.