AI Monetisation

In this episode of the AI Monetisation Podcast, Jayeeta Putatunda, Lead Data Scientist and Director - AI Center of Excellence at Fitch Group, joined Co-founder Binny Mathews, to discuss how financial institutions can successfully evaluate and generate ROI from GenAI initiatives.

Guest Background: A recognized AI leader and NVIDIA Enterprise Platform Advisor, Jayeeta has been named to the AI 100 for GenAI and honored among the Top 25 Visionary Women in FinTech AI. At Fitch Ratings, she leads strategic AI efforts, balancing cutting-edge innovation with the rigors of regulatory finance.

What’s Inside?

• How to evaluate and prioritize high-ROI GenAI use cases in finance
• Building structured GenAI pipelines: From PDF chaos to productivity
• The art of combining causal analysis and LLMs for quantitative accuracy
• Crafting custom evaluation frameworks with business alignment
• Buy vs. Build: Navigating third-party solutions vs. internal development

Key Takeaways:

1. Document processing and customer service are the biggest GenAI ROI drivers in finance

2. Start simple: Evaluate models incrementally and build from real business problems

3. Use SME-guided few-shot learning and lightweight fine-tuning for enterprise accuracy

4. Define evaluation and ROI metrics before building any solution

5. Focus on explainability and expectation-setting to gain business trust and adoption

This episode is essential listening for data science and business leaders looking to implement GenAI solutions in finance with a clear ROI and strong business alignment!

For full show notes, visit- https://bit.ly/44LTTqL

ProjectPro helps you tackle your AI projects with ease. Upskilling the team for specific AI projects, collaborating with experts to co-build AI solutions, or opting for end-to-end project outsourcing, ProjectPro has you covered. With ongoing 1:1 support, enterprises can overcome roadblocks and seamlessly take their projects from PoC to production. Learn more- https://bit.ly/3IIEMFX

In this episode of the AI Monetisation Podcast, Binny Mathews, CEO of ProjectPro explores how AI is revolutionizing instructional design and transforming the future of workforce learning and development.

Our Guest: Julie Stone

We’re joined by Julie Stone, Group Vice President and Chief Learning Officer at TTEC, a global leader in customer experience with over 50,000 employees. Julie brings decades of experience in learning strategy from top organizations like eBay, Prudential Financial, and The Hartford.

What’s Inside?

1. How AI is shifting from traditional training to real-time, personalized, in-the-flow-of-work learning

2. Julie’s flipped learning model in corporate L&D and how it's driving faster proficiency

3. TTEC’s use of AI-powered tools like Curriculum Wizard and Coaching Wizard

4. The convergence of coaching, skilling, and knowledge management

5. Navigating AI adoption barriers like tool overload, governance, and change management

Key Takeaways1. Why average learning fits no one, and how AI enables tailored, task-specific experiences

2. How AI is freeing up human capacity for empathy, creativity, and deeper performance

3. The essential elements of empowerment: value, belonging, and growth

4. Career advice for the AI-native workforce: build durable skills and shape your own journey

This is a must-watch for anyone building or deploying AI in learning and development, especially if you're focused on reducing time-to-proficiency, enhancing learner engagement, and scaling personalized training with measurable ROI.

For full show notes, visit- https://bit.ly/4lFTxYI

ProjectPro helps you tackle your AI projects with ease. Upskilling the team for specific AI projects, collaborating with experts to co-build AI solutions, or opting for end-to-end project outsourcing, ProjectPro has you covered. With ongoing 1:1 support, enterprises can overcome roadblocks and seamlessly take their projects from PoC to production. Learn more- https://bit.ly/3TJZEiv

In this episode of the AI Monetisation Podcast, Boris Tvaroska, AI Technical Lead for Financial Services at Google, joined Co-founder Binny Mathews to discuss how leading financial institutions can build ROI-driven AI co-pilots, while navigating one of the most heavily regulated industries on earth.

Guest Background: With a career spanning Google, AWS, Lenovo, and HP, Boris brings deep expertise in applied AI, NLP, and cloud-based transformation. He’s led AI implementations across global financial enterprises and previously co-founded an NLP startup, giving him a unique perspective at the intersection of innovation and governance.

What's Inside?

1. Top 2 AI use cases in finance: Intelligent document processing & frontline AI copilots
2. Why traditional OCR and RPA fall short in modern financial workflows
3. How banks can scale personalization while managing regulatory risk
4. The role of RAG vs fine-tuning in real-world AI deployments
5. What’s blocking full-scale automation, and how governance must evolve

Key Takeaways:

1. Document-heavy processes are ripe for AI-driven unstructured-to-structured data transformation
2. Copilots can boost efficiency for call centers, loan officers, and advisors
3. Governance, not model performance, is the biggest blocker to adoption
4. Most real-world success comes from RAG + embedding fine-tuning, not full model retraining
5. Regulation needs to catch up to unlock end-to-end automation

This is a must-watch for anyone building or deploying AI in finance, especially if you're focused on measurable ROI, risk mitigation, and scaling innovation responsibly.

For full show notes, visit- https://bit.ly/3GByYNV

ProjectPro helps you tackle your AI projects with ease. Upskilling the team for specific AI projects, collaborating with experts to co-build AI solutions, or opting for end-to-end project outsourcing, ProjectPro has you covered. With ongoing 1:1 support, enterprises can overcome roadblocks and seamlessly take their projects from PoC to production. Learn more- https://bit.ly/4lrlnaR

In this episode, Calista Cooper, Director of Learning and Development at Vendasta, joins Binny Mathews, CEO and Co-founder of ProjectPro, to share how she’s redesigning L&D from the ground up with an AI-first mindset.

What’s Inside?

1. From static courses to dynamic, AI-driven learning flows
2. Rethinking instructional design with generative tools and agents
3. Building personalized onboarding experiences at scale
4. Why learning should happen at the point of need, not in catalogs
5. Upskilling teams on AI tools, systems thinking, and critical prompts
6. Challenges in branded content creation and how Vendasta is solving it
7. Using AI agents as internal “employees” to guide, coach, and support learning

Key Takeaways:

1. Treat AI as a workflow partner, not just a content generator
2. Focus on inputs and business outcomes—AI can handle the outputs
3. Personalized learning isn't about one big LMS—it’s about dynamic context
4. Learning in the flow of work drives stronger engagement and retention
5. Systems thinking is the new must-have skill for an AI-augmented workforce
6. Change management matters; AI agents need thoughtful integration

This episode is essential listening for L&D leaders, instructional designers, and people teams looking to future-proof their learning ecosystems with AI-powered, human-centric design.

For full show notes, visit- https://bit.ly/4lmLAre

ProjectPro helps you tackle your AI projects with ease. Upskilling the team for specific AI projects, collaborating with experts to co-build AI solutions, or opting for end-to-end project outsourcing—ProjectPro has you covered. With ongoing 1:1 support, enterprises can overcome roadblocks and seamlessly take their projects from PoC to production. Learn more- https://bit.ly/3IlvVtz

In this episode of the AI Monetisation Podcast, Anita Luthra, Global Technology Director of AI and Cloud Labs at HCLTech, joins Co-founder Binny Mathews to explore one of the most overlooked challenges in enterprise AI: systemic bias and its multi-billion dollar impact.

Guest Background: A veteran in AI architecture, Anita has led major transformations at JPMorgan Chase, IBM, and now HCLTech. She pioneered the first Watson solution integration at IBM and is a recognized speaker on hallucination and bias in AI, recently featured at the Worldwide AI Summit.

What’s Inside?

1. The trillion-dollar blindspot: How bias infiltrates AI training data and algorithms
2. Real-world implications: Personalization failures and reduced efficacy for diverse users
3. Practical strategies: Detecting and mitigating bias through data, model tuning, and governance
4. Governance in AI: Why accountability lies with every member of the development lifecycle
5. Contrarian AI thinking: Why small models might hold the key to scalable, equitable solutions

Key Takeaways:

1. AI models reflect the societal and demographic imbalances present in their training data

2. Personalization without representation can lead to massive financial and brand risks

3. Bias correction must start early at data selection, architecture, and prompt engineering levels

4. Responsibility for bias mitigation cannot lie with a single team or function

5. Enterprises must rethink traditional hiring and development mindsets to stay relevant in the AI era

This episode is essential listening for enterprise leaders, AI engineers, and product owners looking to build fair, inclusive, and commercially successful AI systems in the real world.

For full show notes, visit- https://bit.ly/44d07Qh

ProjectPro helps you tackle your AI projects with ease. Upskilling the team for specific AI projects, collaborating with experts to co-build AI solutions, or opting for end-to-end project outsourcing—ProjectPro has you covered. With ongoing 1:1 support, enterprises can overcome roadblocks and seamlessly take their projects from PoC to production. Learn more- https://bit.ly/44JxR7W

In this episode of the AI Monetisation Podcast, Cherese James, Senior Manager of Talent Development at Compugen Inc., joins Co-founder Binny Mathews, to explore how AI is reshaping personalized learning, coaching, and leadership development inside modern enterprises.

What’s Inside?

1. How AI is transforming leadership development, feedback, and coaching
2. Using GenAI to localize learning while maintaining global consistency
3. The future of LMS: Will content creation shift to the point of consumption?
4. Why AI can't replace the human touch in coaching—but can amplify it
5. Making adaptive learning and competency modeling practical with GenAI

Key Takeaways

1. AI enables scalable, culturally relevant personalization in learning programs
2. Leadership success now depends on a team-first mindset, not individual performance
3. AI tools can automate tedious tasks, freeing leaders to focus on coaching and strategy
4. L&D teams must embrace curiosity and experimentation to stay ahead
5. Success with AI means creating space for deeper human leadership, not replacing it.

This episode is essential listening for L&D leaders, HR strategists, and people managers aiming to integrate AI into their talent development strategies without losing sight of the human connection that great leadership demands.

For full show notes, visit- https://bit.ly/448YxyV

ProjectPro helps you tackle your AI projects with ease. Upskilling the team for specific AI projects, collaborating with experts to co-build AI solutions, or opting for end-to-end project outsourcing—ProjectPro has you covered. With ongoing 1:1 support, enterprises can overcome roadblocks and seamlessly take their projects from PoC to production. Learn more-https://bit.ly/40kVhhf

In this episode of the AI Monetisation Podcast, Kevin Laughridge, Principal at Deloitte Consulting, joins Co-founder Binny Mathews to delve into how Deloitte and Google are shaping the future of enterprise AI with agentic systems, multimodal platforms, and practical enterprise frameworks.

What’s Inside?

• Agentic AI: How 100+ prebuilt agents are redefining enterprise workflows
• Inside “AgentSpace”: Google’s new single pane of glass for enterprise AI
• The Deloitte + Google + ServiceNow partnership and agent-to-agent protocols
• Building trust-based strategic alliances at enterprise scale
• AI Assist: Deloitte’s full-stack AI solution for accelerating SDLC
• How to measure ROI beyond cost savings, speed, quality, NPS, and more
• The evolving role of humans in an AI-augmented enterprise

Key Takeaways

1. Agentic AI enables exception-based reasoning across enterprise processes

2. Reliable AI outcomes require continuous evaluation and strong guardrails

3. Successful alliances are built on trust, clarity of purpose, and shared value

4. AI adoption is shifting from isolated use cases to full-process optimization

5. Data modernization, not just model performance, is the real bottleneck

6. Enterprise upskilling must include data literacy as a core competency

This episode is essential listening for business and tech leaders navigating enterprise AI transformation, from strategy and tooling to trust and talent!

For full show notes, visit-

ProjectPro helps you tackle your AI projects with ease. Upskilling the team for specific AI projects, collaborating with experts to co-build AI solutions, or opting for end-to-end project outsourcing—ProjectPro has you covered. With ongoing 1:1 support, enterprises can overcome roadblocks and seamlessly take their projects from PoC to production. Learn more- https://bit.ly/461c6Bx

In this episode of the AI Monetisation Podcast, Austin Starks, Founder and CEO of NexusTrade.io, joins Binny Mathews, Co-founder of ProjectPro, to unpack how AI is reshaping investment and trading strategies with automation at the core.

 What’s Inside?

1. From pre-med to solo founder: Austin’s unconventional path to fintech innovation
2. AI + Natural Language: Automating trading strategies without writing code
3. Why Rust? Engineering a high-performance backtesting engine
4. Real-time financial analysis with LLM-generated SQL
5. Growth hacking NexusTrade via TikTok and Medium
6. What makes AI effective in swing vs. intraday trading

 Key Takeaways

1. Focus on problems, not ideas. AI is most powerful when solving real user pain points
2. Using LLMs for trading works best when paired with structured tools like SQL
3. Educational UX is essential to onboard non-experts into AI-based platforms
4. Open-ended agentic AI in finance isn’t fully production-ready but structured workflows are
5. 5. A fast, solo-built AI stack is feasible if you’re relentlessly focused and love to code

This episode is a must-listen for fintech builders, AI engineers, and investors looking to understand how LLMs are transforming the future of trading.

For full show notes, visit-https://bit.ly/4dXBJVM

ProjectPro helps you tackle your AI projects with ease. Upskilling the team for specific AI projects, collaborating with experts to co-build AI solutions, or opting for end-to-end project outsourcing, ProjectPro has you covered. With ongoing 1:1 support, enterprises can overcome roadblocks and seamlessly take their projects from PoC to production. Learn more- https://bit.ly/43KVvkc

In this episode of the AI Monetisation Podcast, Jayney Howson, Senior Vice President of Global Learning and Development at ServiceNow, joined Co-founder Binny Mathews to share how ServiceNow is transforming enterprise learning through AI and the science of play.

Guest Background

With 20+ years of experience spanning marketing, sales, and talent development, Jayney leads global learning initiatives at the $200B software leader. Previously at Salesforce, she supported over 30,000 team members and now spearheads ServiceNow University, a bold new platform delivering AI-powered, personalized, in-the-flow learning at scale.

What’s Inside?

✅ The vision behind ServiceNow University and how it powers AI-driven, personalized learning

✅ Science of play: How neuroscience and gamification help overcome fear and drive real skill-building

✅ AI Coaches & Playground Environments: What modern learning looks like at scale

✅ How ServiceNow embeds learning in the flow of work with context-sensitive, just-in-time content

✅ The bold idea of a “Human Renaissance” — unlocking creativity through automation

Key Takeaways:

1. Personalization and context are non-negotiables in enterprise learning

2. True growth happens in psychologically safe, exploratory environments

3. Learning must shift from static content to adaptive, AI-generated skill development

4. Strong data foundations are essential for tracking performance and enabling tailored upskilling

5. Future talent strategies must account for early-career learning disrupted by AI automation

This episode is essential listening for L&D leaders, talent strategists, and enterprise executives looking to harness AI to unlock deeper human potential at work.

For full show notes, visit- https://bit.ly/4jzLdYv

ProjectPro helps you tackle your AI projects with ease. Upskilling the team for specific AI projects, collaborating with experts to co-build AI solutions, or opting for end-to-end project outsourcing—ProjectPro has you covered. With ongoing 1:1 support, enterprises can overcome roadblocks and seamlessly take their projects from PoC to production. Learn more- https://bit.ly/4jGosSJ

In this episode of the AI Monetisation Podcast, Yao Fehlis, Head of AI at Artificial, Inc., joins Co-founder Binny Mathews to explore how Self-Driving Labs are transforming scientific discovery through automation and AI.Guest Background: With a background spanning neuroscience, biotechnology, and AI, Yao leads the charge at Artificial, Inc. in designing autonomous lab systems that accelerate the pace of experimentation. His work sits at the intersection of robotics, machine learning, and life sciences, thus bringing the vision of automated R&D closer to reality.

What's Inside?

1. What exactly is a Self-Driving Lab, and how does it work?
2. Automating hypothesis generation and experimental design
3. Real-world applications in biotech, pharma, and materials science
4. The AI stack powering lab automation—from simulation to orchestration
5. Ethical implications and the future of autonomous scientific research

Key Takeaways:

1. Self-driving labs can drastically reduce the time and cost of experimentation

2. Combining robotics and AI enables closed-loop scientific workflows

3. Domain expertise remains essential for guiding and validating automated systems

4. Modular, interoperable lab setups are key to scalable automation

5. The future of science will be hybrid, with humans and machines collaborating in real-time

This episode is a must-watch for researchers, technologists, and innovators eager to understand how AI and automation are reshaping the scientific method itself.

For full show notes, visit- https://bit.ly/3Z4w1vn

ProjectPro helps you tackle your AI projects with ease. Upskilling the team for specific AI projects, collaborating with experts to co-build AI solutions, or opting for end-to-end project outsourcing—ProjectPro has you covered. With ongoing 1:1 support, enterprises can overcome roadblocks and seamlessly take their projects from PoC to production. Learn more- https://bit.ly/45tlLAA