MONETIZING DATA & AI INVESTMENTS
Unlock the full potential of your data and AI investments
AI has become dramatically more accessible today
While Neural Networks and Machine Learning have been in commercial use for a couple of decades, AI overall has become dramatically more accessible today. Firms today don’t need armies of AI scientists to realize the benefits of AI in their business operations. Reasoning AI has reduced hallucination, making LLMs more ready for commercial use. Additionally, the popularity of Agentic AI has now made the monetization of AI much easier.
While the opportunity is immense and well understood, there are a few obstacles that need to be overcome:
- Data – A lot of data, while immensely valuable, may not be captured today, or be captured in a fragmented, unreliable way. e.g., you may have several salesforce instances, the sales processes may not be ensuring diligent data entry, data taxonomies may be inconsistent, other relevant data (e.g. product, financials, service) may not be readily accessible.
- Models – Any AI models used need to be vetted for regulatory compliance, cyber security, biases, data privacy, hallucinations, etc.
- Operating model – Should you own and develop? Which models have the potential to be your secret sauce (think TikTok). These should be built, tuned, enhanced inhouse. What are the external data sources that can provide you an edge especially in serving your customers and prospects?
- Costs – While general purpose LLMs have gotten cheaper the overall investments in cloud infrastructure, data management and model management can escalate quickly. Several firms have unintentionally ended up in a log jam, while their AI centers-of-excellence build aspirational enterprise-wide data and AI infrastructure.
- Monetization – Most firms have already benefited from small, tactical deployments of AI. Now is the time to monetize AI in a way that helps you leapfrog the market. What are the most impactful use cases? How do you ensure that the results are revolutionary, rather than evolutionary?
Kepler Cannon helps industry leaders:
- Inject AI intelligence into traditional business decisions (e.g. prospecting, dispatching, matching leads to sales personnel)
- Gather, enrich, cleanse, integrate underlying data to extract intelligence for day-to-day operations
- Adopt, adapt and develop fit-for-purpose models for higher efficacy
- Realize benefits by transforming business processes with access to AI intelligence
- Develop & deliver transformational AI monetization strategies
Client Successes:
- Gen-AI based prospecting tool that built a targeted 16,000+ asset manager lead database
- AI-enabled workforce uberification tool for 35,000+ staff across 60+ locations processing 500+ skill tags and levels
- 2.8x increase in client conversion through feature engineering
- Inhouse analytics platform to democratize data & models for 4,000+ users
78%
banks have implemented data monetization strategies
executives are unsure how to deploy AI
30%
Gen AI projects are abandoned due to poor data quality, unclear business value and inadequate risk controls
Perspectives: Monetizing Data & AI Investments
AI Needs a Translator
As AI models become increasingly commoditized, sustainable value comes from translating institutional knowledge into AI-ready workflows, governance, and operating models. Organizations that bridge this gap move beyond isolated pilots to achieve…
From Interface to Intelligence
The next frontier of digital commerce is not better checkout, but better coordination. This whitepaper examines how agentic AI is transforming fragmented transactions into intelligent, autonomous experiences - and what businesses must do to stay…
AI on Your Terms
Despite widespread AI adoption, most organizations struggle to move from pilot to production because they focus on tools before clearly defining the business problem, governance requirements, and operating model. This paper outlines a business-first…
AI Chaos to Control – Managing Multi-Tool Governance at the SDLC Level
The SDLC-first governance model represents a fundamental shift in how organizations approach AI governance. Rather than treating governance as a set of controls applied to individual AI tools or platforms, this model embeds governance directly into…
Value Realization in the Age of AI – Capturing ROI across the AI Lifecycle
In this environment, the ability to continuously realize, measure, and communicate customer value is not optional. Value realization has evolved from a customer success activity into a strategic, cross-functional discipline that determines whether…
From Concrete to Capital – Monetizing Your Datacenters in the AI Era
The global datacenter industry is undergoing a structural transformation unlike anything seen since the cloud computing revolution of the 2010s. Artificial intelligence in particular has made compute infrastructure a hot commodity, driving demand…
Scoring the Unscored – Alternate Data for Credit Scoring
Alternate data can meaningfully expand who is “scoreable” by capturing financial behavior that bureaus miss. In the U.S., this directly targets the credit-invisible population (and a wider thin-file segment), creating a material inclusion unlock at…
In Search of the Perfect Digital Dollar
As digital assets redefine financial infrastructure, the benchmark for money is shifting beyond stability to include real-time settlement, yield, and seamless transferability. The institutions that deliver this balance will shape the next generation…
Who is getting into Stablecoins- Corporate Treasurers
While blockchain transforms the infrastructure of financial markets, the principles of investor protection and securities regulation remain constant. The path to scalable tokenization is defined not by new rules, but by new ways of complying with…
Same Rules, New Rails: The SEC on Tokenized Securities
New rails don't rewrite the rules—they redefine how efficiently they're executed. Tokenized securities represent an evolution in market infrastructure, where innovation succeeds only when paired with regulatory certainty.
A last thought on Mythos: How much is Marketing and how much is reality?
As enterprise AI matures, competitive advantage will depend less on bold claims and more on demonstrable execution. The gap between marketing and measurable value is where long-term winners will emerge.
How Tokenization is quitetly rewriting Capital Markets
Capital markets are moving beyond digitization toward true programmability. Tokenization is enabling a future where assets are more liquid, transactions are seamless, and financial infrastructure is built for a 24/7 digital economy.
Bot and Sold – What executives and consumers must get right as AI starts to spend money
The next wave of enterprise value will come not from AI that generates insights, but from AI that autonomously executes work. Agentic AI shifts the focus from isolated task automation to goal-driven workflows, reducing coordination overhead while…
When Agentic AI Becomes Reality – Foundational Principles to Enterprise-scale Execution
The greatest productivity gains from AI will come from reimagining how workflows—not simply automating existing processes. Competitive advantage will belong to organizations that redesign workflows around outcomes rather than individual tasks.
Govern the Data, Scale the AI – A Lifecycle Framework for Trusted, AI-Ready Data
Competitive advantage in the AI era will depend less on algorithmic sophistication and more on the ability to transform enterprise data into trusted, governed, and reusable assets. Strong data foundations are what enable AI to scale responsibly.
The Algorithmic Buyer – An AI operating System for Modern Procurement
As procurement grows more complex, competitive advantage will depend on turning data into real-time intelligence. AI is enabling organizations to shift from manual processes to proactive, scalable procurement that drives measurable business value.
Beyond the Breach – Why Cyber Resilience Demands AI
In an era of AI-powered cyber threats, resilience depends on the ability to anticipate, adapt, and respond in real time. Organizations that integrate AI throughout their security operations will be best positioned to safeguard trust and continuity.
AI(lignment) in Service Management – Bridging Service Delivery and Intelligent Automation through GenAI
A future in service management that does not include AI is all but unimaginable. Organizations that use AI as part of their service management already report a 40-60 percent reduction in the mean time to resolution and up to an 80 percent decrease…
I Spy with My Little AI – Understanding and Implementing Next-Gen Agents
As the financial industry moves toward increased automation, early adopters of agentic AI will gain a competitive edge by reducing operational costs and improving service delivery.
A One-Time Opportunity in Recurring Charges – Capitalizing on Subscription Management
The world has seen a revolution in payment models for goods and services spurred by a huge shift from one-time payments to recurring revenue models. Subscriptions are no longer just about convenience—they're a financial ecosystem that both empowers…
The AI Bottom Line – Transforming Customer Service with AI
Customer support is at the forefront of AI adoption due to its ability to solve acute challenges in the process. Over 85% of organizations are investing in AI to improve business functions and customer service is the second highest priority for…
The Future of SaaS: Innovation or Extinction?
The rapid rise of Generative AI (Gen AI) is fundamentally reshaping the B2B SaaS landscape, presenting challenges for traditional software providers that have long dominated the market.
AI on the Money – Personalization and Loyalty through AI-driven Offers
AI in customer loyalty isn’t just a phase, but an inevitable evolution. The emerging wave of AI adoption in customer loyalty is set to transform the global payments industry.
Can You Trust Your KPIs? – Building Trust in Metrics That Drive Performance
Performance management has become unwieldy in the era of AI and big data. As performance data proliferates, and access to insights becomes more open, leaders must revisit their approach to performance measurement.
Accelerating Tokenization of Payments – Re-Examining an Established Service
Payment tokenization has existed since the early 2000s and is now becoming pervasive due to the growth in digital payments. We talk about the complexities and challenges of implementing tokenization, as well as the benefits of successful…
Clean Data, Clear Outcomes – Enhancing Healthcare Processes through Data Integrity
In healthcare, accurate data is not just a luxury—it is a necessity, essential for operational success and improved patient outcomes.
Transformation Readiness
70% of all planned transformation initiatives fail to deliver tangible business value and 84% of organizations fail at tech transformations in particular.
Navigating the Data-Driven Economy
Data is often treated as an IT function and is not fully utilized, leading to compromised data quality and availability. A CDO is responsible for creating a data-driven culture across the organization, ensuring that the right data is collected,…
Blockchain and B2B Finance
Digital deflation is the most effective way for businesses to manage through today’s environment of high inflation, currency fluctuations, potential recession, and labor shortages. Effective sourcing and third-party technology resource usage is key…
AIn’t No Sunshine – Tackling AI Risks
As AI becomes increasingly central to value creation, it also presents some concerns. Instances of AI exhibiting problematic behavior have become more frequent, raising apprehensions about fairness, privacy, accuracy, and security.
Smart Procurement, Smarter Profits
In a competitive business environment, high-performing CPOs are 18x more likely to fully deploy AI/cognitive capabilities. This typically leads to 92% faster demand forecasting, on average 350 man-hours are saved through automation, and there is a…
Cockpit for Digital Transformation
This paper outlines a framework for creating a digital dashboard to help CIOs and other digital leaders track their progress and success in digital transformation initiatives. It includes practical guidance on how to define and measure key metrics,…
Monetizing Your Data
Companies are increasingly turning to data monetization strategies to capitalize on new opportunities and revenue streams. This paper offers a comprehensive guide to data monetization, including strategies, considerations, and industry examples.
Client Loyalty 2.0
We are on the cusp of a revolution within financial services that will have far-reaching ramifications for the +1 billion unbanked, current models of financial intermediation across entities and borders, and ultimately the very nature of how…
Trends in Digitalization of Insurance
For some, Insurance might seem a monolithic industry, but for the ones keeping a close eye on it- Insurance is revamping itself faster than ever! From days when underwriting a simple policy would take weeks and months, to now when it can be done in…




































