Artificial intelligence is reshaping how companies reach customers, but the focus around automation often overshadows the fact that AI can just as easily create costly mistakes as it can generate growth. Daniel Saks, serial entrepreneur and CEO of Landbase, has spent his career helping companies unlock growth through smarter go-to-market strategies.
“AI isn’t magic,” Saks says. “It’s only as good as the strategy behind it.” Drawing from his experiences scaling AppDirect into a unicorn and now pioneering AI-driven approaches at Landbase, Saks argues that the difference between failure and success comes down to how businesses design, train, and implement their AI.
Context Over Content
Many organizations rely on generic tools that churn out campaigns misaligned with customer needs or brand identity. “AI models don’t fail because they lack intelligence. They fail because they lack context,” says Saks, whose team at Landbase addresses this by building domain-specific models tailored to go-to-market challenges. His team built GTM-1 Omni, an AI trained specifically for go-to-market strategy. The system is designed to generate recommendations grounded in business realities, rather than generic assumptions. By embedding deep contextual knowledge, companies can prevent the disconnect that often plagues off-the-shelf solutions.
Human in the Loop
The promise of full automation is tempting, but Saks cautions against letting machines run without oversight. Whether it’s pricing, messaging, or targeting, even minor missteps can carry major consequences. “The best AI systems are designed for collaboration. You want to give your teams the ability to audit, tweak and override decisions,” he says. Saks champions a collaborative design where humans remain central to the process. Human-in-the-loop approaches build trust, protect brand reputation, and ensure AI becomes an accelerator of growth rather than a liability.
Measuring What Matters
Activity does not always equal results. Companies that judge their AI by the number of leads generated risk filling pipelines with low-quality prospects. “The key is aligning your AI to real outcomes like booked meetings, closed deals, or reduced cost of customer acquisition,” he explains. At Landbase, AI systems adapt in real time, learning from performance data to refine campaigns toward meaningful results. This outcome-driven design ensures that organizations maximize value from every interaction rather than drowning in irrelevant activity.
Building Smarter, Not Faster
The future of AI-powered go-to-market strategies is not about pushing machines to do more, but about using intelligence to do better. Contextual models, collaborative oversight, and outcome alignment create the conditions for sustained revenue growth while minimizing costly errors. “AI isn’t just the future of go-to-market, it’s the present,” Saks says. “But it’s not about doing more with machines, it’s about doing better with intelligence.”
Saks’ perspective reflects a blend of hard-earned entrepreneurial lessons and forward-looking innovation. Having scaled global companies and advised Fortune 500 leaders, his conviction is that the businesses that thrive will be those that blend human creativity with machine intelligence in practical, outcome-focused ways.
For more insights from Daniel Saks, follow him on social media on LinkedIn and X (formerly Twitter), or visit his website.
