At our recent exclusive event at Batch LDN – The Batch Members Club, London, on February 11, 2026, industry leaders and CXOs gathered to decode the rapidly evolving landscape of artificial intelligence. As Net Solutions founder Sameer Jain noted in his opening remarks, “AI is everywhere, but no one really has the right model or roadmap to implement it”. To bridge this gap, Net Solutions introduced the Growth Engineering model, built on a continuous cycle of discover, engineer, optimize, and scale. As AI transforms consumer touchpoints, Sameer emphasized that businesses must move like a “pit stop crew,” evolving platforms on the fly to remain relevant.
The event, hosted by our CRO, Andrew, provided a comprehensive deep dive into the technology, data, and cultural shifts required to thrive in the era of AI. Here is a synthesis of the insights shared by our speakers and panelists.
The Shift to Agentic Commerce: Are You Visible to the Machines?
Speaker: Sartaj Rajpal, Head of AI Research at Profound
Sartaj opened the session with a stark warning: traditional search is losing market share, and the age of human commerce is ending as the age of machine commerce begins. He highlighted that AI agents are transitioning from merely recommending products to autonomously executing purchases on behalf of consumers. In fact, AI-influenced purchase volume already sits at $104 billion annually.
When a user asks an AI model a question, the engine fans out the query, searches the web, and decides who to trust in just three seconds. To ensure your brand isn’t invisible to these models, Sartaj advised moving beyond traditional SEO metrics, which only account for a fraction of AI citations. Instead, CXOs must prioritize:
- Structured, Answer-First Content: AI engines favor semantic URLs, up-to-date content, and comparison pages over generic AI-generated filler.
- Earned Media & Social Proof: Reddit is currently the most-cited source in AI search, followed by YouTube. Models prioritize natural human discussions and fresh data over pure domain authority.
“In just three seconds, you are either invisible or you are the answer.” – Sartaj Rajpal, Profound
People, Process, and Culture in the Age of AI
Speaker: Alfred Biehler, Former Head of Innovation at Google
While Sartaj covered the technological shift, Alfred pivoted to the human element, emphasizing that successful innovation requires the right culture. He cautioned leaders against pursuing AI projects simply to increase profit, noting that while money is the “oxygen” of a business, it is not its purpose. AI models must be grounded in reality and designed to solve real consumer problems.
Alfred challenged the CXOs in the room to solicit diverse perspectives from their frontline employees. He emphasized the importance of psychological safety, noting that innovation requires celebrating “failures” as learning opportunities rather than punishing them.
The Panel: Data, Trust, and the Omnichannel Experience
The event culminated in a panel discussion featuring Sartaj, Adrian Blair (CEO of Trustpilot), and Andrew Zeni (Founder of Nobody’s Child and Fabocus).
- Social Proof as AI Engine Fuel: Adrian Blair explained that LLMs love social proof because it provides the recent, long-tail data they need to answer highly specific user queries. Trust in the agentic era will be built on transparency and credibility, with AI increasingly relying on authoritative platforms like Trustpilot to gauge authority.
- Structured Data and Digital Product Passports: Andrew Zeni discussed how his businesses are pioneering the use of structured data. By implementing Digital Product Passports (DPPs) that detail product traceability and compliance, his brand, Nobody’s Child, has elevated customer trust, resulting in a 3.4x increase in online basket value from £36 to £124.
- The Rebirth of Physical Retail: Despite the rise of digital agents, Zeni stressed the enduring value of human experience. Anticipating increased digital acquisition costs, he recently signed for six new physical stores, noting a direct correlation between local physical presence and localized online transactions.
Audience Q&A: Addressing CXO Challenges
Interactive sessions sparked highly strategic questions from attendees, revealing practical hurdles:
- Overcoming Innovation Bureaucracy: When attendees voiced concerns about bureaucracy and ROI pressures, Alfred advised building “guardrails” that make it easier for employees to experiment in a sandbox. He also stressed the importance of deliberately scheduling “thinking time” away from screens.
- Ideation and Skill Gaps: To address employees’ fear of AI, the panel suggested rewarding value creation. Andrew Zeni shared how he guaranteed his team’s job security on the condition that they use AI to drive efficiencies and double the business without increasing headcount.
- The Role of Backlinks in AI: Sartaj clarified that while backlinks are less important for direct LLM citations, they still help brands rank on Google, which overlaps with AI indexing.
- Brand Loyalty vs. Agentic Price Wars: Attendees raised concerns about AI agents prioritizing price over loyalty. The panel responded that as agents get smarter, they will adopt nuanced user preferences, including loyalty program memberships.
- Investment Strategy: When asked where to invest a hypothetical £10, Zeni offered a clear directive: Stop building your own enterprise software. Instead, invest in creating pristine, structured product data and leverage best-in-class third-party tools.
Next Steps: The Growth Readiness Diagnostic
The prevailing takeaway was clear: brands must prepare today for an AI-driven tomorrow. To assist with this transition, Net Solutions announced a “Growth Readiness Diagnostic”.
This rapid, interview-based assessment evaluates an organization’s commercial goals, AI visibility, data foundations, and operational execution to provide CXOs with a prioritized roadmap for success.
To wrap up the insights from this executive briefing, we invite you to take the first step toward future-proofing your business.
Take Action: Evaluate Your AI Maturity
Through this diagnostic, we help you assess:
- Commercial Objectives: Aligning AI initiatives with your core business value and purpose.
- AI Visibility: Measuring how your brand currently performs in “Answer Engine” citations.
- Data Foundations: Ensuring your product data is structured and trusted for machine learning customers.
- Execution & Operations: Optimizing your internal culture and processes for continuous innovation.
