V2RSION founder Paul Evans warns ad tech positioning strategy is failing

The immediate implication is that ad tech firms relying on AI for go-to-market messaging risk becoming invisible as their value propositions blend into a generic industry baseline. In the broader streaming and advertising ecosystem, this homogenization makes it harder for buyers to distinguish between vendors, potentially slowing down the adoption of new tools. As LLMs become the primary discovery layer for B2B procurement, companies must provide context-rich signals to ensure they are surfaced in AI-driven recommendations. Watch for whether firms begin integrating sustainability metrics back into their core AI narratives to differentiate their operational efficiency from competitors.

V2RSION operates in a B2B ad tech landscape where differentiation has become a central concern as AI-generated content floods buyer-facing channels. The company's emphasis on strategic positioning aligns with broader industry observations about programmatic automation risks creative sameness in programmatic and ad tech vendor messaging. Blue Planet and Telefónica Deutschland completed a joint proof of concept using agentic AI to power 5G network slicing services, demonstrating how infrastructure vendors are already embedding AI agents into operational workflows to create measurable efficiency gains that distinguish their offerings from competitors. While that deployment sits in telecom rather than ad tech, it illustrates the same dynamic Evans describes: when AI tools become table stakes, the companies that survive are those with clearly articulated strategic narratives rather than generic capability claims. The business case for differentiation in B2B technology markets is sharpening as AI compresses the time between product launch and competitive parity. Ericsson's approach to monetizing AI-driven network improvements offers a parallel. Ericsson's networks chief Per Narvinger noted at MWC 2026 that AI models can squeeze 10% more value from spectrum assets that have been optimized deterministically for 30 years, allowing operators to optimize existing infrastructure without hardware replacements. That subscription model, where value is framed in concrete performance metrics rather than vague AI promises, mirrors the positioning discipline Evans advocates for ad tech firms. The Ericsson Mobility Report from June 2025 further noted that gen AI traffic represents only 0.06% of total network data traffic currently, yet uplink demand is growing faster than downlink due to generative AI interactions, signaling that the infrastructure underpinning AI-driven discovery and content is still in early stages, giving B2B vendors a window to establish differentiated positioning before the market matures. The technical and strategic implications for ad tech firms extend to how AI agents are reshaping procurement and vendor evaluation. Narvinger's observation that AI can improve a 30-year-old deterministic algorithm by 10% underscores how even mature, well-understood systems yield unexpected gains when AI is applied with clear strategic intent. For B2B ad tech companies like V2RSION, the lesson is that positioning must be grounded in specific, quantifiable outcomes rather than broad AI capability claims. As automated AI ad campaigns increasingly mediate vendor discovery and procurement decisions, firms without documented positioning risk being filtered out entirely by AI systems that prioritize structured, differentiated signals over undifferentiated noise. Recent pilots further highlight how these automated systems are already shifting the competitive landscape, even as research suggests that industry trust in these autonomous tools remains split.