From Gen AI Hype to Real AI Impact – Key Takeaways from Aviso’s Latest Webinar
Mar 26, 2025
Artificial Intelligence, particularly Generative AI, has dominated conversations in sales and go-to-market (GTM) strategies. But amidst all the buzz, how do companies distinguish between AI’s real impact and overhyped expectations? This was the central theme of Aviso’s recent webinar, "From Gen AI Hype to Real AI Impact: Embracing AI Adoption with Human Collaboration."
Featuring Max Tarasevich, SVP of Sales at Aviso, and David Dulany, Founder & CEO of Tenbound, the discussion explored how AI and Gen AI in particular, is reshaping sales performance, streamlining workflows, and redefining traditional sales roles. The webinar provided a clear roadmap for sales leaders looking to leverage AI effectively while ensuring a seamless balance between human expertise and AI-driven insights.
Applying "Jobs to Be Done" Theory in Sales: A Smarter Approach
The rise of AI in sales isn’t just about automation, it’s about reshaping how sales teams operate. David emphasized the importance of viewing AI’s role through the lens of Clayton Christensen’s Jobs to Be Done (JTBD) framework. Instead of merely adopting tools, sales teams should think of AI as a solution they "hire" to complete essential tasks more efficiently.
Sales professionals juggle a vast array of responsibilities, from prospecting and data entry to pipeline management and strategic decision-making. The JTBD approach helps sales leaders pinpoint where AI can make the biggest impact by streamlining workflows and optimizing productivity.
Applying the JTBD Framework to Sales:
Identify the Core Jobs to Be Done – Outline the essential tasks sales teams perform daily.
Analyze Time Allocation – Determine where SDRs, sales reps, and managers spend the most time.
Prioritize ATL vs. BTL Tasks – Separate high-impact, strategic tasks (Above the Line) from repetitive, operational tasks (Below the Line).
Leverage AI to Optimize Workflows – Automate BTL tasks so sales teams can focus on high-value activities.
By applying this framework, AI takes over repetitive, time-consuming tasks, allowing sales professionals to focus on high-value activities. For example, SDRs can leverage AI to automate research and pull accurate contact details, significantly reducing time spent on prospecting. Sales reps benefit from AI-driven insights extracted from financial reports and earnings calls, eliminating the need for manual data gathering. At the leadership level, AI provides predictive analytics, enabling executives to make data-driven decisions based on deal patterns and customer behavior.
Bottom Line: Sales leaders must rethink traditional workflows and pinpoint areas where AI can enhance productivity and decision-making. By integrating AI into sales processes, companies enable their teams to spend more time building relationships and closing deals, the areas where human expertise truly makes the difference.
The Role of Data: AI is Only as Good as the Inputs
AI has the power to accelerate sales processes, but without high-quality data, it can just as easily amplify inefficiencies. The principle of "Garbage In, Garbage Out" is especially relevant in AI-driven sales. If poor data is fed into AI systems, the result isn’t improved performance—it’s just bad decisions made faster.
One key example is AI-driven prospecting. The promise was hyper-personalized outreach at scale, but in many cases, AI has simply increased the volume of generic, low-value sales messaging, leading to more spam and lower engagement rates. Instead of driving better customer interactions, poor-quality data has caused brands to burn credibility with prospects.
For AI to truly improve sales performance, companies must prioritize data accuracy and integrity from the start:
Clean, structured data ensures AI makes meaningful recommendations.
Well-curated prospect lists prevent AI from generating irrelevant or spammy outreach.
Continuous data validation helps AI-driven sales strategies remain effective over time.
The key takeaway? Before implementing AI, sales leaders must invest in high-quality data to avoid scaling inefficiencies. AI is a force multiplier—but only if it has the right inputs to work with.
From SDR-Heavy to AI-First: The Rise of GTM Engineering
Traditional sales teams have long relied on large Sales Development Representative (SDR) teams to manually generate leads, conduct research, and handle prospecting. However, with AI automating much of this groundwork, modern sales organizations are shifting to an AI-first model that prioritizes efficiency and strategic hiring.
Go-To-Market (GTM) Engineering is emerging as a key function in this transformation. Rather than maintaining extensive SDR teams, companies are now investing in GTM Engineers who can integrate AI-driven tools, streamline workflows, and ensure clean data flows into the sales process.
By adopting a leaner structure, where a GTM Engineer works alongside a select group of top-performing SDRs, businesses can scale smarter. This shift emphasizes quality over quantity, optimizing resources for maximum impact while enhancing efficiency and precision in sales execution.
Key shifts in AI-first sales teams:
AI automates repetitive SDR tasks, reducing the need for large prospecting teams.
GTM Engineers ensure AI workflows are optimized, preventing inefficiencies like "garbage in, garbage out" data issues.
Fewer SDRs, more high-impact roles, with sales reps focusing on relationship-building rather than manual research.
The takeaway? Sales leaders should rethink hiring strategies, shifting from SDR-heavy structures to AI-driven teams that maximize efficiency and revenue impact.
Breaking the Myths: What AI Can Really Do for Sales & Marketing
As AI adoption skyrockets, misconceptions about its capabilities continue to hold back marketing and sales leaders. Max shared compelling insights drawn from McKinsey and HBR findings, highlighting five persistent Gen AI myths that have shaped, and often limited, how sales and marketing leaders perceive Gen AI.
From generating dynamic account plans to automating pre-meeting briefs, AI is transforming every stage of the sales cycle. Max shared a compelling example of a Fortune 200 company where sellers were spending an average of 30 hours per account just gathering insights. AI can now consolidate CRM data, external news, and past interactions into a strategic plan, reducing this workload dramatically.
Rather than viewing AI as just another tool, modern businesses are integrating it into their workflows to optimize efficiency at every stage of the sales cycle. This is where Aviso’s AI Agents and Agentic Workflows come into play. Designed to automate routine tasks, provide real-time insights, and assist teams in making data-driven decisions, these AI-driven solutions help organizations move beyond outdated assumptions.
Another key discussion point was tackling data security and AI hallucinations, two major concerns for enterprises. Max detailed how Aviso’s unique approach combines generative AI with non-generative AI to ensure accuracy, reliability, and data protection.
Want to learn how to challenge these myths and unlock AI’s full potential for your go-to-market teams? Watch the full webinar for exclusive insights and real-world applications, and check out Tenbound for consultation and deep insights into over 3500 sales technology products and services.
