#34- Wouldn't It be NAIce: Reshaping Buyers Journey with AI, Win with AI, AI Tutoring Outperforms, o1 IQ levels, CueCard AI
Jonathan M K.
GTM & AI Performance & Strategy Executive | Board AI Advisor | Strategic Enablement & Performance | Business impact > Learning Tools | Proud Dad of Twins
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Some AI posts from this last week in case you missed it:
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AI Revolution in Sales: How Digital Sales Rooms and AI Are Reshaping the Buyer's Journey
Had a blast talking with Gal Aga . This guy's been in the sales game for 17 years and knows what he is talking about. If you have not or do not follow him, click on his name and follow him NOW.
They created Aligned which is your digital sales room on steroids. For those of you not familiar, think of it as a virtual workspace where buyers and sellers can collaborate throughout the entire sales process. No more scattered emails and lost attachments. Everything's in one place, making it easier for buyers to make decisions and for sellers to guide them through the process.
But here's where it gets really interesting – they've added AI to the mix. This isn't about replacing salespeople; it's about making them more effective. The AI can answer buyer questions, organize information, and even give salespeople a heads-up when a deal might be going south. It's like giving your sales team superpowers.
We also talked about how this might change sales roles. Gal thinks some entry-level positions might evolve, but he sees a future where salespeople become more like project managers and experts. They'll focus on the complex parts of deals that AI can't handle.
What really got me excited was Gal's vision for the future. He's talking about bringing together data from emails, calendars, and buyer interactions to give salespeople insights they've never had before. Imagine knowing exactly when to loop in an executive or being able to predict when a deal's in trouble.
The founders are ex sales guys who are laser focused on creating a product that actually helps the buyers journey and sellers experience. And from what Gal shared, it's going to make selling smarter, more efficient, and more buyer-focused. Whether you're in sales or just curious about how AI is changing business, this is something you need to keep an eye on. It's an exciting time, and I can't wait to see where this technology takes us.
Highlight:
Key Quotes from Gal:
"We realized that the difference is, what they're doing, they're really good at first managing the complexity of the sales process, multi threading project management. So the more the better sellers really are more project managers and their enablers, and they know how to handle all of the moving parts."
"We look at ourselves as a broader scope, both for customer success. A lot of our 40 percent of our customers are actually not salespeople. And are in partnerships, SDR, customer success. So it's more of a customer collaboration platform."
"I don't think that AI will replace fully salespeople and I think that it can... I think that, okay let's talk. There are a few levels, SDRs, a lot of the things that we're doing Yes, AI can do and it doesn't make sense to, to have SDRs doing forever."
"A single space that the seller organizes for you really helps orchestrate that buying journey. Okay, it helps you as a champion looping these people that can now see, wow, okay, I can see all of the, I can see the competitive comparison and it's a table and it's embedded there in the room."
"These things, when you combine CRM data with the asynchronous interaction between the buyer and the seller And all of the behind the scenes buying journey and you take email in and you bring in calendar meetings, that could be a goldmine for decision supporting insights of how to execute the process for forecasting as well."
Why Selling Is Harder Today and How to Succeed and WIN in the Gen AI Era
Jonathan Moss found this amazing article from Andreessen Horowitz regarding the trials of sales today and how to WIN with AI.
Selling software today is more challenging than it was a few years ago, with shrinking opportunities and a competitive landscape dominated by Generative AI (GEN AI). Key factors contributing to this difficulty include macroeconomic uncertainty, post-COVID SaaS consolidation, and the early stages of GEN AI adoption. However, over 85% of winnable IT spend lies outside of industries immediately disrupted by GEN AI, meaning there are still significant opportunities for startups that target medium- and long-term industries preparing for GEN AI’s impact.
Why GTM Professionals Should Pay Attention
GTM professionals face the dual challenge of navigating a smaller market and rising competition from gen AI-native startups. Understanding how to segment the market and win customers outside of immediate-gen AI sectors is crucial. Selling to companies in medium- and long-term sectors requires a sophisticated sales approach, including strong product roadmaps, demonstrating ROI, and focusing on how AI fits into their future strategies.
Practical Applications for GTM Professionals
1. Targeting Medium and Long-Term Opportunities: Most IT spend today is from companies preparing for gen AI’s impact in the next 2–3 years. GTM teams can focus on these sectors (e.g., manufacturing, ecommerce) by emphasizing how their solutions address current pain points and help future-proof their businesses against gen AI disruption.
2. Demonstrating ROI: CIOs prioritize software that delivers measurable ROI. Instead of selling on experimentation, focus on concrete business cases that show cost savings or revenue growth, positioning your solution as a long-term investment.
3. Enterprise Sales: Product-led growth alone is no longer sufficient. GTM teams must engage in traditional enterprise sales motions, which involve heavy engagement with CFOs and CIOs. Tailor your sales pitch to fit into the customer's existing ecosystem, making it easier to justify investment in your product.
How Different Teams Can Adapt
1. Sales
- Use Case: Sales teams must focus on selling high and developing enterprise-level relationships. Tailored, value-driven pitches to CIOs that emphasize ROI and gen AI-readiness are essential in today’s environment.
- In Depth: Prioritize building relationships with decision-makers and emphasize how your product integrates seamlessly with existing tools, mitigating risks while offering growth opportunities.
2. Customer Success
- Use Case: Customer Success teams can focus on helping clients extract maximum value from their existing stack, ensuring customers see clear ROI from the products they’ve invested in.
- In Depth: Regular check-ins and proactive support to help clients maximize efficiency will be critical, especially as companies consolidate their SaaS investments and seek more value from existing tools.
3. Marketing
- Use Case: Marketing teams should focus on creating content and campaigns that highlight the ROI of their solutions, showing how they help businesses prepare for future gen AI integration without requiring immediate investment.
- In Depth: Emphasize how your product aligns with long-term business goals and supports gradual, rather than immediate, AI adoption.
4. Enablement
- Use Case: Enablement teams can support sales by providing resources that demonstrate real-world use cases for clients preparing for AI disruption, ensuring sales teams are equipped with relevant, value-driven messaging.
- In Depth: Ensure that the sales team is aligned with the company’s product roadmap and understands how to position the product’s long-term value in a rapidly evolving market.
5. Business Development
- Use Case: Business Development teams can leverage this shift by partnering with companies focused on medium- and long-term AI impacts. Identifying and forming alliances with these companies early can secure strategic opportunities.
- In Depth: Target potential partners who may be slower to adopt gen AI but have long-term growth plans that your product can support, helping them navigate the evolving tech landscape.
6. HR
- Use Case: HR teams need to be mindful of how AI integration is transforming internal tools and processes. Helping organizations understand the long-term benefits of incorporating AI while managing costs will help drive employee adoption and efficiency.
- In Depth: HR can also focus on recruiting AI talent or upskilling employees to ensure the workforce is ready for the AI-driven transformations that are on the horizon.
Selling in today’s market is undeniably more difficult due to economic uncertainty and the rise of gen AI, but GTM professionals who focus on understanding customer pain points, tailoring their approach to medium- and long-term opportunities, and emphasizing measurable ROI will still find success. The key lies in crafting a sophisticated, enterprise-level sales approach that positions your product as essential for navigating the complexities of AI integration in the coming years.
The AI Tutoring Revolution: A Game-Changing Study
This groundbreaking study , conducted at Harvard University, compared AI tutoring to active classroom learning in a college physics course. The results were nothing short of revolutionary: AI-powered instruction led to more than double the learning gains in less time compared to traditional in-person teaching methods. Not only did students learn more efficiently, but they also reported higher levels of engagement and motivation when working with the AI tutor.
The researchers took great care in designing the AI system, incorporating established pedagogical best practices to ensure a fair comparison to high-quality in-person instruction. This wasn't a case of pitting a generic chatbot against human teachers; rather, it was a carefully crafted AI tutor designed specifically for educational purposes. The study employed a rigorous crossover design with nearly 200 students, providing robust evidence of a large, statistically significant advantage for AI tutoring.
One of the key benefits of the AI approach was its ability to provide personalized, self-paced learning experiences. Students could move through the material at their own speed, spending more time on challenging concepts and quickly progressing through familiar ones. This level of customization is difficult, if not impossible, to achieve in a traditional classroom setting, even with the best active learning techniques.
About the study:
1. Sample size and group division:
- The study had a total of 194 participants
- They were divided into two nearly equal groups: Group 1 (N=96) and Group 2 (N=98)
2. Gender distribution:
- Both groups had a majority of female students
- Group 1: 69.5% female, 30.5% male
- Group 2: 65.8% female, 35.2% male
3. Academic year distribution:
- The majority of students in both groups were second-year students (62.6% in Group 1, 60.8% in Group 2)
- There was also a significant proportion of fourth-year students (25.2% in Group 1, 26.2% in Group 2)
4. Academic concentration:
- The majority of students in both groups were life science majors (54.8% in Group 1, 55.7% in Group 2)
- Undeclared majors were the second largest group (27.0% in Group 1, 29.3% in Group 2)
5. Prior knowledge assessment:
- The Force Concept Inventory (FCI) pre-test and a midterm exam were used to assess students' prior knowledge
- There were no statistically significant differences between the groups in these measures
6. Study design:
- The study used a two-lesson crossover design
- Each group experienced both the experimental (AI tutor) and control (active learning classroom) conditions across the two lessons
领英推荐
7. AI tutor system:
- A screenshot shows the interface of the AI tutor system
- It includes a question statement at the top, with space below for student input and AI tutor feedback
Key stats:
Learning Gains:
- Students in the AI-tutored group learned more than twice as much compared to those in the active learning classroom.
? This means that for the same content, students using the AI tutor demonstrated understanding and retention at more than double the level of their peers in traditional classes.
Time Efficiency:
- The median time spent by students in the AI group was 49 minutes, compared to 60 minutes for the in-class group.
? This indicates that the average AI-tutored student completed the lesson 18% faster than those in the classroom.
- 70% of students in the AI group completed the material in less than 60 minutes.
? This shows that the majority of AI-tutored students finished more quickly than the fixed classroom time.
Student Engagement:
- On a 5-point Likert scale, students rated their engagement with the AI tutor at 4.1 (SD = 0.98), compared to 3.6 (SD = 0.92) for the active lecture.
? This suggests that students felt significantly more engaged with the AI tutor, with the difference being about half a point on the scale.
Student Motivation:
- Students rated their motivation when working on difficult questions at 3.4 (SD = 1.0) with the AI tutor, versus 3.1 (SD = 0.86) for the active lecture.
? While smaller than the engagement difference, this still indicates higher motivation levels when using the AI tutor.
Statistical Significance:
- The difference in post-test scores between the AI and active lecture groups was highly significant (p < 10^-8).
? This extremely low p-value indicates that the chances of these results occurring by random chance are less than one in 100 million, providing strong evidence for the effectiveness of AI tutoring.
Effect Size:
- The effect size of AI tutoring ranged from 0.73 to 1.3 standard deviations, which is considered large in educational research.
? In education, an effect size of 0.4 is typically considered practically significant. These values, being well above that threshold, represent a substantial improvement in learning outcomes.
Study Design:
- The study involved 194 students in a crossover design over two lessons.
? This sample size and design provide robust data, with each student experiencing both AI and traditional instruction, allowing for direct comparison and control of individual differences.
These statistics, along with their explanations, provide a comprehensive view of the study's findings, highlighting the significant advantages of AI tutoring in terms of learning outcomes, efficiency, and student experience.
Implications for Go-to-Market Professionals
For go-to-market professionals, these findings signal a potentially massive shift in the education and training landscape. The results suggest a growing market for AI-enhanced learning products that can deliver personalized, on-demand instruction across various subjects and industries. This presents exciting opportunities to develop new offerings or enhance existing products with AI tutoring capabilities.
The study also underscores the importance of thoughtful AI implementation that adheres to educational best practices. Simply deploying chatbots or generic AI assistants is unlikely to yield the same impressive results. This insight is crucial for GTM professionals looking to enter or expand in the educational technology space.
Moreover, the success of AI tutoring in a challenging subject like physics suggests that this approach could be effective across a wide range of disciplines. From corporate training programs to professional development courses, the potential applications are vast and varied.
Strategic Shifts and Market Opportunities
In light of these findings, GTM professionals should consider several strategic shifts to capitalize on this emerging trend:
1. AI-Powered Product Development: Investing in the development of AI-powered learning features or standalone products could provide a significant competitive advantage. This might involve building proprietary AI tutoring systems or partnering with existing AI providers to integrate advanced learning capabilities into your offerings.
2. Repositioning Existing Products: There's an opportunity to reposition existing educational or training products to highlight AI-enhanced learning capabilities. Even if your current offerings don't include full AI tutoring, emphasizing any personalization or adaptive learning features could help align with this growing trend.
3. Strategic Partnerships: Explore partnerships with educational institutions, content providers, or AI technology companies to expand your reach and capabilities. These collaborations could help you quickly enter new markets or enhance your existing products with cutting-edge AI tutoring features.
4. Market Expansion: The effectiveness of AI tutoring opens up possibilities for expanding into new educational markets or adjacent industries. Consider how your products or services could be adapted to serve different learning environments, from K-12 education to professional certifications.
5. Customer Experience Focus: Prepare for changing customer expectations around personalized, adaptive learning experiences. This might involve redesigning user interfaces, implementing more sophisticated progress tracking, or offering AI-powered study recommendations.
6. Thought Leadership: Position your company as a thought leader in the AI-enhanced learning space by producing content, speaking at conferences, or participating in industry discussions about the future of education and training.
Future-Proofing Your Go-to-Market Strategy
By embracing these trends early, companies can position themselves at the forefront of what could be a major disruption in education and corporate training markets. The potential for AI to dramatically improve learning outcomes while reducing time investment is too significant to ignore.
However, it's important to approach this opportunity thoughtfully. The study emphasizes the importance of incorporating sound pedagogical principles into AI tutoring systems. GTM professionals should work closely with educational experts and instructional designers to ensure their AI-enhanced products truly facilitate effective learning, rather than just providing flashy tech features.
Additionally, consider the potential challenges and objections that might arise as AI tutoring becomes more prevalent. Address concerns about data privacy, the role of human teachers, and the importance of social interaction in learning environments proactively in your marketing and product development efforts.
In conclusion, this study represents a pivotal moment in the evolution of education and training. For go-to-market professionals, it offers a roadmap to significant new opportunities. By leveraging the power of AI tutoring, companies can offer more effective, engaging, and personalized learning experiences to their customers, potentially revolutionizing how knowledge is acquired and skills are developed across various industries.
Maxim Lott goes through his analysis and the IQ results of the new o1 Preview:
Massive breakthrough in AI intelligence: OpenAI passes IQ 120
I recently came across an article about OpenAI's new model, "o1," and it feels like a turning point in AI development. The article details how "o1" was put through its paces on the Norway Mensa IQ test, and the results blew past my expectations. Scoring 25 out of 35, this model didn’t just perform well—it outpaced the human average by a solid margin and left other AI models in the dust. What’s particularly interesting is that this wasn’t a fluke. The author made sure to include fresh, offline IQ questions that weren’t part of any training data, and yet "o1" still performed remarkably well. This eliminates the concern that the AI is just regurgitating pre-learned data—it’s actually reasoning.
The implications of this are massive. On the good side, we're now looking at AI that isn’t just automating tasks but is stepping into the realm of higher-order thinking. For GTM professionals, this could completely change the way we leverage AI. We’re no longer talking about basic automation or data handling—this is AI capable of sophisticated decision-making, pattern recognition, and even strategic reasoning. Imagine the potential in real-time analytics, forecasting, or even customer interactions. It’s becoming clear that AI is going to become a much more integral part of decision-making processes.
But this also comes with serious implications. If AI is evolving this quickly, we’re not far from it surpassing many human cognitive abilities. That raises a tough question: how do we maintain control over these tools while still using them to their fullest potential? We’re moving toward a future where AI could outperform human intelligence in critical areas, and that’s both exciting and unsettling. For instance, if AI starts handling more of the strategic thinking, where does that leave the human role in GTM teams? Will we need to adapt to managing these advanced systems rather than making the decisions ourselves?
And there’s a practical side we can’t ignore—while AI is clearly improving in reasoning, it’s still not perfect. "o1" got some questions wrong, even though its logic was sound. That means we can’t fully rely on it without some oversight, but how long will that be true? The article predicts that in just a few years, we could see AI models with IQs around 140, which is higher than most humans. By 2026, we could be looking at machines smarter than the people running them. If this pace keeps up, we’re on track for an AI revolution that will shake up every industry, especially for those of us working in GTM roles.
In short, this article was a wake-up call. The rapid progress of AI is something we need to be paying attention to—not just because it’s fascinating, but because it’s going to fundamentally change how we operate. Whether that’s for better or worse depends on how we handle this evolution.
Key Stats and Points:
- o1's Performance: Scored 25/35 on the Norway Mensa IQ test, surpassing human averages and previous AI models.
- Comparison to Humans: Human readers of the blog averaged an IQ score of 103 on similar tests.
- Offline Test Results: A new, offline-only IQ test showed similar performance from "o1," indicating genuine reasoning improvement.
- AI IQ Projections: Based on prior models (Claude-1, Claude-2, Claude-3), AI is expected to reach IQ 140 by 2026.
- AI Reasoning: The article demonstrates that AI’s ability to analyze patterns suggests it’s evolving into higher-order reasoning beyond simple data prediction.
Takeaways for GTM Professionals:
1. AI is progressing rapidly: The leaps in AI reasoning abilities indicate that automation tools will continue to evolve, meaning professionals in GTM roles must stay adaptive and integrate advanced AI systems into their workflows.
2. AI as a strategic tool: AI isn’t just for automation—it’s becoming capable of sophisticated problem-solving. GTM professionals should leverage AI for decision-making processes, recognizing its capacity to handle complex reasoning tasks.
3. Anticipate faster developments: With AI models like "o1" showing exponential growth, GTM strategies must account for near-future improvements, especially in AI-driven insights and analytics.
4. Potential for AI-driven innovation: As AI intelligence grows, businesses can harness it for product innovation, customer insights, and competitive advantages. The trajectory of AI advancement offers opportunities for GTM professionals to spearhead cutting-edge approaches.
5. Industry Implications: AI is not just a support tool but a game-changer. GTM professionals should be prepared to see more AI-powered offerings in the market, which may disrupt traditional roles, requiring new skill sets and strategies to remain competitive.
GTM AI TOOL OF THE WEEK: Cuecard.ai
CueCard.ai positions itself as a powerful AI-driven sales enablement tool designed to streamline the entire sales process by enhancing collaboration between sales and marketing teams. The platform equips sales reps with quick, real-time access to critical product information, competitive insights, and marketing content.
CueCard’s key features include RFP automation, content impact tracking, and AI-powered sales battle cards, all designed to reduce inefficiencies and help teams close deals faster. The solution also provides an AI-powered co-pilot that draws from an organization’s knowledge base, ensuring that sales reps can answer complex questions from prospects quickly and accurately. CueCard is engineered to boost sales velocity by centralizing resources, eliminating delays in information retrieval, and automating follow-ups.
Benefits:
- Sales Enablement: CueCard provides dynamic Battle Cards that keep sales teams updated on competitors and product information in real time, ensuring efficient responses in sales conversations.
- RFP Automation: Streamlines the Request for Proposal (RFP) process by automatically generating accurate responses using AI, saving hours of manual work.
- Content Impact Tracking: Tracks the performance of marketing content and its direct impact on sales outcomes, offering 100% visibility into how content drives conversions.
- Sales Knowledge Hub: Centralizes sales materials, making them accessible in just a few clicks, speeding up the process of finding necessary resources during a sales cycle.
- AI-Powered Responses: CueCard’s AI assistant provides real-time answers to prospect questions, pulling from integrated knowledge bases such as Google Docs, YouTube, and soon, platforms like Notion and Confluence.
Key Takeaways for GTM Professionals:
1. Efficient Information Flow: CueCard removes friction between sales and marketing by providing fast, accurate access to knowledge and resources. This means less time wasted hunting for information and more time spent on actual selling.
2. Enhanced Sales Collaboration: The platform improves collaboration between teams by giving both sales and marketing complete visibility into how content is being used and its effectiveness, ensuring alignment across departments.
3. Sales Velocity and Automation: With features like RFP automation and AI-driven follow-up email generation, CueCard helps sales teams keep momentum and respond faster to prospects, reducing the sales cycle length.
4. AI as a Sales Co-Pilot: CueCard goes beyond basic automation. It offers an AI co-pilot that can provide immediate, tailored responses during interactions, pulling from the company’s internal resources. This ensures that sales reps can focus on closing deals rather than gathering information.
5. Real-Time Insights: CueCard’s ability to provide real-time competitor intelligence and track content performance means GTM professionals can make more informed, data-driven decisions, improving overall sales strategies and outcomes.
This platform is ideal for teams looking to streamline sales operations, enhance collaboration, and leverage AI to close more deals faster. The automation of RFPs and the power of a real-time AI assistant are game-changers for GTM professionals looking to stay competitive in a fast-paced market.
Ok my friends, that is all for today, let me know what you think!
AI Founder & Advisor | Exponential Growth for Enterprises | 4x Exits
1 个月Love the GTM AI focus. The Demo Tools Library is a fantastic resource!
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| HR Leader & Founder | I help you build your brand and skyrocket audience | 375K+ | Helped 500+ brands on LinkedIn | Organic LinkedIn Growth | Author |900M+ content views | Lead Generation | Influencer Marketing
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CFI | Finance | Business & Investments | Barclays | S&P Global | Helping CEOs, Founders and Investors to build strong personal brand on Social media | Personal Brand Strategist | 2 times top 200 creators by Fevikon
1 个月Wow, what a great lineup for this week's GTM AI Podcast and newsletter! I'm particularly interested in learning more about how AI is changing the buyers journey with Gal Aga from Aligned.