This episode of the AI to ROI podcast, hosted by Ray Rike and Peter Buchanan, explores how leading SaaS companies are surviving the "SaaSpocalypse" - a massive market cap devaluation triggered by the rise of AI. The hosts break down the transition from traditional SaaS to AI-first models, emphasizing that simple "feature bloating" isn't enough; companies must undergo a fundamental "organ replacement" of their architecture, pricing, and culture.

The discussion deep-dives into three success stories:

• Notion: Transformed from a document suite into an agentic execution platform through strategic acquisitions, moving toward autonomous workflows.
• Canva: Democratized design by making AI features invisible and intuitive, resulting in a 700% increase in AI tool usage and massive revenue growth.
• ServiceNow: Leveraged its 20-year history in workflow automation to pivot from seat-based pricing to task-based pricing, using AI agents to orchestrate complex enterprise processes.

If you are a SaaS company executive looking for great examples of how they transitioned to be AI-first - this episode is full of great examples, strategies, and tactics.

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In this episode, our host Ray Rike sits down with Jacco van der Kooij, founde and CEO, Winning by Design, to discuss the real-world deployment of "Jack" - an AI SDR that has spent the last 12 months redefining the front line of Go-To-Market (GTM) strategy. Jacco shares the "AHA" moments and hard truths discovered while moving beyond human constraints like slow response times and inconsistent qualification. Discover how treating an AI SDR (agent) as a "system" rather than a "product" initially led to 2,030 conversations, 100% CRM capture, and a $200,000 deal.

Episode Summary

Winning by Design set out to prove that if AI can handle the high-risk, high-empathy role of an SDR, it can work anywhere in GTM. Over the course of a year, their AI agent, Jack was built on a foundation of 1mind logic and Clay enrichment. The agent evolved from a simple chatbot into a trained GTM operator.

Key Highlights:

• Breaking Human Constraints: The project addressed critical issues like burnout, limited global coverage, and poor CRM hygiene that even the best human reps struggle to maintain.
• The "AHA" Moments: Jacco details how the team realized Jack shouldn't just "chat" but perform industrial-scale qualification while supporting buyers in their buying journey.
• The Power of Iteration: Initial surprises, such as a low 8% email capture rate, were overcome by designing a better "value exchange" rather than just tweaking prompts.
• Tangible Results: After refinement, email capture jumped to 20%, MQL conversion rose by 36%, and the system successfully captured nearly 9,000 SPICED answers.
• The Ultimate Do’s and Don’ts: Success requires anchoring the agent in a GTM system and iterating weekly; failures stem from treating AI like an unstructured chatbot or deploying without clear ownership.

The Do's

• Design the value exchange first: Ensure the AI provides something useful to the buyer before asking for information
• Earn the next step: Focus on providing enough value to merit the next stage of the conversation
• Anchor the agent in your GTM system: AI should scale a pre-designed, structured system rather than an improvised process.
• Start narrow, then expand: Focus on one specific motion and one outcome before attempting to scale.
• Iterate weekly: Small, frequent changes to the system drive the most significant gains in performance.
• Focus on the buyer's journey: Design the experience to help the buyer buy, rather than just helping the seller sell.

The Don'ts

• Treat AI like a chatbot: Avoid unstructured "chatting," as it kills conversion rates; focus on industrial-scale qualification instead.
• Chase volume over quality: Remember that activity is not the same as a healthy pipeline.
• Hide the AI behind humans: Be transparent about using an AI agent to build trust with the buyer.
• Deploy without ownership: AI implementation is a Go-to-Market responsibility, not just an IT project.
• Expect AI to fix a bad process: AI will not fix poor GTM design; it will only expose and amplify existing flaws.
• Point AI at unstructured data: Do not simply point the AI at a massive folder of research; start with specific, high-quality training materials.

If you are considering deploying agentic AI into your Sales organization and process, this episode is full of great insights, experiences, and measurements for your AI investment in Sales.

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Are we witnessing a productivity revolution or the greatest labor displacement in history?

In this detailed episode of AI to ROI, Peter Buchanan and Ray Rike break down the "Great AI Jobs War," a period of massive upheaval where corporate gleefulness meets workforce anxiety. They move past the "AI washing" to find the real metrics that define success in the age of intelligence.

Key Discussion Points:

• The Historical Context: Ray draws parallels between the AI revolution and past disruptions like the Industrial Revolution, the cotton gin, and the assembly line, noting that AI is moving with a magnitude and speed never seen before

• The "Mother May I" Productivity Gap: While 47% of S&P 500 companies now discuss AI in earnings calls, only 10% are seeing meaningful ROI, leaving a "staggering" 56% of companies getting "little to nothing" out of their implementations

• The Million-Dollar Employee: A deep dive into Klarna’s radical transformation—reducing headcount from 5,000 to 3,000 through attrition while doubling revenue to reach the "magic number" of $1.1 million in revenue per employee

• The War on Early Careers: Why entry-level IT hires have plummeted from 25% to 7% of all hires, and the "structural problem" of junior roles requiring 2–3 years of experience because AI is now doing the "digital grunt work"

• Blue-Collar as the "Gold-Collar" Future: Why the CEO of NVIDIA suggests young people skip computer programming for mechanical trades, and how salaries for AI-related construction and electrical roles have doubled

• Customer Service Autonomy: How Bank of America's "Erica" handled 2 billion interactions with a 98% resolution rate in under 44 seconds, signaling a massive shift in how businesses handle scale

Actionable Insights for Leaders:

• Measure Revenue Per Employee: This is the ultimate metric for AI productivity.
• Bake AI Aptitude into Hiring: Every new white-collar job description should require "AI curiosity" and applicable tool skills.
• Strategic Augmentation: The goal isn't just headcount reduction, but using the "free cash flow" from AI efficiencies to build a war chest for growth and sales.

To read more details and subscribe to the AI to ROI Newsletter for more data-driven strategies on turning AI hype into bottom-line results.

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In the second episode of AI to ROI: The Big Story, Ray Rike and Peter Buchanan analyze the critical transformation required for traditional SaaS companies to become AI-first organizations. With the SaaS industry generating $273 billion annually, the hosts warn that incumbents are under "two-front" attack: internal refactoring of legacy systems and external disruption from hyper-efficient AI-native startups.

Key Highlights of the Episode:

• The "SaaS to AI" Pivot: Ray compares the current shift to the on-premise-to-SaaS transition of 20 years ago, noting that today’s change requires a fundamental rewrite of an operating culture rather than just adding "AI veils" like prompt engines

• The Rise of AI-Native Efficiency: Peter highlights companies like Lovable and Cursor, which have achieved hundreds of millions (or billions) in valuation in under a year with minimal staff, challenging the traditional SaaS model of linear employee growth

• The Shift in Financial Metrics: The hosts discuss the new economic reality: forgetting 80% gross margins in favor of a 50-65% range to account for high token and inference costs. Success will depend on the "COGS to CAC" model, offsetting higher infrastructure costs with dramatically lower customer acquisition costs via AI automation

• A Roadmap for Success: To fight back, SaaS incumbents must re-architect around outcomes rather than features. This includes leveraging their "crown jewel data" and status as systems of record to build decision intelligence layers that AI-native startups lack

• The HubSpot Success Story: Ray details how HubSpot successfully scrapped its 2023 roadmap within weeks of ChatGPT’s launch, shipping AI-native products in under 90 days and moving toward a "Results-as-a-Service" future

• Advice for Leaders and Employees: Ray suggests that CEOs must re-engineer every department to be AI-first, while employees should commit to learning new AI tools every month to remain employable in an increasingly automated landscape.

Listen to the full episode for a deep dive into how to avoid becoming an "orphan" SaaS company in the age of Agentic AI.

You can read the newsletter edition covering this topic by clicking here.

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In this episode of the AI to ROI podcast, host Ray sits down with Drew Laxton, CFO at Outreach, to explore the profound transformation of sales technology and financial metrics in the age of AI. Drew shares the strategic reasoning behind his return to Outreach, driven by a conviction that the company is uniquely positioned to lead the next era of agentic AI and automated revenue workflows.

The conversation goes beyond the hype, offering a masterclass in how finance leaders must adapt to a software landscape that is moving from seat-based subscriptions to consumption-driven models. Drew provides an inside look at how Outreach is re-engineering its own financial playbook to account for the high compute costs and non-linear revenue growth associated with AI.

Key discussion points include:

• The "Personal Productivity" vs. "Financial ROI" Debate: Why the initial wave of AI efficiency must eventually translate into higher quotas and lower OpEx to satisfy the board.
• Maintaining Margins in an AI-Native World: A deep dive into the "triumvirate" of Product, Engineering, and Finance that manages gross margins as compute costs replace traditional SaaS overhead.
• The Metric Recalibration: Why traditional SaaS snowballs don't work for AI, and how Outreach is using "spend-as-truth" to normalize data for NRR and CAC calculations.
• Agentic AI in Action: How Outreach's "revenue agents" are replacing manual prospecting with autonomous, data-tuned interactions that learn from previous customer engagement.

Some Key Insights and Quotes pulled from the conversation with Drew:

On the "Boring" Wins of AI: While many look for revolutionary shifts, Drew emphasizes the value in automating the mundane:

"A lot of the AI tools that I’ve seen so far... there's kind of boring outcomes that are very impactful... like our QA process within the coding side has very much streamlined."

On the Changing Economics of SaaS: Drew acknowledges that AI-native products fundamentally alter the 80%+ gross margin expectations of the past decade:

"We do need to bring gross margin into our understanding of SaaS tools because it's just not the same... You've got to be more efficient on the go-to-market side to make the economics work."

On the Rise of Consumption Pricing: The shift to variable pricing means the "snowball" metric of the past is no longer sufficient:

"What is your ARR has become a lot more challenging question than it used to be... consumption is not linear on these products. It’s kind of zero, very little, and then a lot."

On the Importance of Usage Over Revenue: In a variable world, product utilization becomes the primary indicator of a healthy business:

"Product utilization... becomes a core signal to retention. It's not just revenue anymore, it's utilization month by month... spend is truth."

Advice for Aspiring CFOs: For those looking to reach the C-suite in the AI era, Drew suggests one primary trait:

"Be curious. Just be curious about everything... Ask questions, get time with the CFO or the leaders of the various organizations... wanting to understand their business has only benefited me."

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In the first episode of the AI to ROI: Big Story podcast, our co-hosts Peter Buchanan and Ray Rike discuss the emerging importance of Context Graphs in AI Software.

Why are context graphs suddenly being called a trillion-dollar opportunity in enterprise AI? In this inaugural episode of The Big Story, hosts Ray Rike (CEO of Benchmarkit) and Peter Buchanan (Managing Partner of New Plan) dive into the "glue technology" that fills the missing gap in the AI stack.

While traditional knowledge graphs tell you what happened, context graphs reveal the why! Context Graphs capture the decision traces, policy constraints, and precedents that make AI agents truly auditable and trustworthy. From preventing "data breakage" in regulated workflows to revolutionizing supply chain quality control, discover why context is the key to moving AI from experimental pilots to reliable production.

Key Takeaways

• The Why Behind the Action: Context graphs provide the connectivity that agentic AI lacks, recording who made a decision and under what specific constraints.
• A Trillion-Dollar Value Add: Industry leaders believe context is a massive economic value driver for companies in the era of AI.
• Beyond Knowledge Graphs: Moving from simple data points to decision lineages that explain the "why" behind an event.
• Real-World Use Cases: Deep dives into data governance at firms like Vanguard and Prudential, and quality control in the automotive supply chain.
• The Vendor Landscape: Discussion on current players like Atlan, Neo4j, and Writer, and why tech giants like Microsoft and Salesforce are the "lurkers" to watch.
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Timestamps

• 00:00 Introduction to the AI to ROI podcast series.
• 02:40 Defining Context Graphs: The missing gap in the AI stack.
• 04:15 The Trillion-Dollar Opportunity: Economic value vs. market size.
• 06:30 Knowledge Graphs vs. Context Graphs: Moving from "what" to "why".
• 09:20 Who should care? Roles from the CEO to the Chief Risk Officer.
• 12:45 Use Case 1: Data Governance and preventing "downstream breakage".
• 15:10 Use Case 2: Unifying the Go-To-Market (GTM) stack.
• 18:30 Use Case 3: Supply chain visibility and automotive quality control.
• 21:40 The Market Map: Current leaders and "Lurker" strategies from Big Tech.
• 25:50 Executive Summary: Things every leader must do right now.

Context graphs are a key component to turn Agentic AI software vision into Agentic AI explainability!

Read the AI to ROI Newsletter on Substack to dive deeper into this week's Big Story!

Subscribe at: ai2roi.substack.com

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Welcome to the first episode of AI to ROI, the newly re-imagined evolution of the highly successful Metrics That Measure Up podcast. In this launch episode, our host, Ray Rike sets the stage for a new era of conversations focused on turning artificial intelligence from hype into measurable business outcomes.

The inaugural guest is Todd Olson, Founder and CEO of Pendo, who joins the show for an interactive, unscripted discussion on how companies should measure the real impact of AI agents inside modern SaaS and cloud organizations. Together, they explore how AI-driven “digital workers” are reshaping productivity, workflows, and operating models across the enterprise

Key topics include how companies can measure the performance and business impact of AI agents, the emerging metrics that define agent adoption and activation, and why connecting usage data to tangible outcomes like time saved, cost reduction, and revenue impact is critical for ROI. Todd also shares his perspective on outcome-based pricing, why it remains rare in AI-native software today, and what must change for it to scale.

The conversation wraps with a forward-looking discussion on SaaS and AI convergence, as agents increasingly appear on org charts and product roadmaps, followed by practical advice on developing AI competencies for the next generation of business leaders.

If you care about moving beyond AI experimentation toward measurable economic value, AI to ROI is your new go-to podcast.

Subscribe, rate, and follow AI to ROI on your favorite podcast platform.

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The world of FP&A is having its day in the spotlight. New pricing models, a new focus on near real-time business planning, the increased focus on balancing revenue growth and profitability, coupled with the dynamic impact that AI is having on the SaaS market, are all making the role of FP&A a more strategic asset. Albert Gozzi, is the founder and CEO of Aleph, a modern FP&A platform and company that recently raised $29M in their Series B financing from Khosla Ventures.

During today's episode, our host, Ray Rike is joined by Albert Gozzi, Founder and CEO Aleph, to discuss the strategic future of FP&A including:

• The vision behind founding Aleph
• The evolution of AI in FP&A
• FP&A’s role in developing corporate strategy
• Growth strategies being used in a crowded category

If you are a finance leader, FP&A professional or fellow B2B SaaS founder with a product purpose built for the Office of Finance, this conversation with Albert Gozzi is full of unique insights, ideas and opportunity to make your Financial Planning and Analysis organization a strategic asset!

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