Summary of "The birth of Services-as-Software: Phil and Karthik (KK) usher in the new era of the workplace"
Summary: “The birth of Services-as-Software: Phil and Karthik (KK) usher in the new era of the workplace”
This conversation between Phil First and Karthik (KK), CEO of Ascendion, explores the transformation of the services industry amid the rise of AI—particularly agentic AI—and the shift toward outcome-driven business models. The discussion covers leadership, organizational culture, capital allocation, talent, and strategic imperatives for services firms navigating this evolving landscape.
Key Business Themes & Frameworks
Market Evolution & AI Adoption
- 2025 marked the emergence of “agentic AI at work,” moving beyond experimental AI to practical, autonomous capabilities integrated into business processes.
- There is a distinction between personal AI empowerment (widespread individual adoption of tools like ChatGPT) and professional AI adoption, which is hindered by organizational silos and leadership gaps.
- The “AI velocity gap” describes the lag between personal AI use and enterprise-wide AI transformation.
Leadership & Culture
- Leadership debt/crisis: A gap exists between employee expectations for AI adoption and actual leadership behavior.
- Trust is the new currency in AI-driven transformation; leaders must be purposeful, empathetic, and relentless to bridge the gap between doers and leaders.
- Essential leadership qualities include optimism, courage, empathy, hands-on involvement, and fostering psychological safety to encourage experimentation and learning.
- A culture shift from process-driven to learning-driven organizations is critical.
- Leaders must have “technological comfort,” able to build and demo AI solutions themselves, and embrace commercialism akin to product companies.
Organizational & Operational Tactics
- Medium-sized businesses are uniquely positioned to serve enterprises by balancing scale, flexibility, and innovation agility.
- Enterprises are increasingly dissatisfied with legacy service providers tied to rigid contracts and slow innovation.
- Overcoming fear of change is a major barrier for clients and organizations in switching providers or adopting new AI-driven models.
- The industry needs to transition from charging for effort (headcount/time) to charging for outcomes, emphasizing:
- Revenue acceleration
- Profit maximization
- Enhanced experiences
- Risk mitigation (“keeping your CEO out of jail”)
Strategic Frameworks & Playbooks
- Engineering for the Power of AI: A method combining platform, delivery playbook, and specialized people (“agentic delivery managers”) to deliver four key outcomes:
- Revenue acceleration
- Profit maximization
- Enhancing experiences
- Risk mitigation/compliance
- The delivery playbook is nuanced for multiple use cases and environments, emphasizing outcome acceleration over technology hype.
Capital Allocation & Financial Metrics
- Capital allocation models in services must evolve to be more like product companies—investing significantly in IP, platforms, and innovation rather than just operational expenses.
- Headcount is becoming an irrelevant metric; focus should shift to revenue per FTE and operating margin per FTE.
- A proactive sales approach is critical: 87% of deals are proactively shaped, with competition entering late in the sales cycle.
- Innovation funding in services is currently inadequate compared to product companies; this needs to change to avoid erosion of profitability.
Talent & Skills
- New leadership profiles require a blend of:
- Traditional service mindset: client-centric problem ownership, flexibility, empathy.
- Technical hands-on skills: ability to build and lead AI agent development.
- Commercial acumen: ability to productize and commercialize AI platforms.
- Storytelling skills: borrowing from the movie industry to better communicate outcomes and value.
- Learnability and curiosity: continuous skill development and adoption of new technologies across all functions (finance, marketing, sales).
- Breaking down organizational silos and fostering cross-functional collaboration is essential.
Industry Outlook & Market Opportunity
- The services industry is not shrinking but evolving; it can grow 6-7x by embracing platform-based, IP-centric models that decouple revenue growth from headcount growth.
- The industry is the “last mile” connecting technology to business outcomes.
- Market fragmentation remains high: top 15 players hold only ~30-40% of a $1.5-$2 trillion market, leaving significant opportunity for innovation and new entrants.
- The shift from legacy linear models to platform-enabled autonomous delivery models is key to capturing the large untapped market.
Investor Perspective
- Investors are increasingly focused on leadership quality, IP investments, and defensible “secret sauce” (platform differentiation).
- Traditional metrics like headcount and scale are less relevant; output-to-input ratios and operating margin per FTE are better indicators of success.
- Success metrics must evolve to reflect outcome delivery and capital efficiency.
- The term “Services-as-Software” reflects the blending of service delivery with software/platform models, emphasizing outcome over method.
Concrete Examples & Case Studies
- A sales example where a competitor sends multiple PowerPoint decks to explain their platform, while Ascendion’s sales team demos the platform live on an iPad within 15 minutes, building trust and credibility.
- Large multi-million dollar deals with Fortune 100 companies focused on transforming software development for accelerated outcomes.
- Enterprise clients stuck in legacy fixed-price contracts express fear of switching to innovative partners despite clear benefits.
- Comparison of AI adoption to prior automation waves (e.g., RPA in 2012), highlighting differences in scale, maturity, and leadership commitment.
Actionable Recommendations
For Leadership
- Lead from the front with hands-on AI use and development.
- Build trust through transparency and honest conversations about AI’s impact on jobs.
- Foster psychological safety and cross-functional collaboration.
- Invest in leadership development that combines empathy with relentless curiosity and courage.
For Organizations
- Shift from effort-based to outcome-based commercial models.
- Productize platforms and integrate IP as a core business asset.
- Develop a delivery playbook tailored for AI-driven outcomes.
- Break down silos and encourage shared learning and storytelling across teams.
- Proactively shape deals early, focusing on value and risk reduction.
For Investors
- Focus on leadership quality, IP investment, and platform defensibility.
- Use revenue per FTE and operating margin per FTE as key KPIs.
- Support companies that prioritize capital allocation toward innovation and platform development.
Key Metrics & KPIs Mentioned
- 87% of deals are proactively shaped before competition enters.
- Market size: $1.5-$2 trillion services market with top 15 companies holding 30-40% share.
- Industry potential to grow 6-7x by embracing platform/IP-centric models.
- Capital investment in innovation for large clients is currently very low.
- Tech debt: ~$2 trillion; process debt: ~$4 trillion; total enterprise debt: ~$10 trillion (contextualizing operational inefficiencies).
- Increasing focus on revenue per FTE and operating margin per FTE as relevant financial metrics.
Presenters / Sources
- Phil First – Host, From the Horse’s Mouth, HFS Research
- Karthik (KK) – CEO of Ascendion, industry veteran and thought leader on AI and services transformation
This discussion highlights a pivotal moment for the services industry, emphasizing leadership, culture, and outcome-driven innovation as the keys to thriving in the AI-powered future of work.
Category
Business
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