How AI is Reshaping Retail and Financial Services - Commerce Ventures
How AI is Reshaping Retail and Financial Services
Gen AI is already driving down costs in our industries, with the promise of transforming experiences in the future.
Generative AI is already making waves across the Commerce Continuum. We’ve created two decks outlining our overall point of view. Those two decks can be found here:
Generative AI for FinTech
Financial services is rapidly evolving with the advent of Generative AI (Gen AI). This technology holds the potential to help financial institutions increase automation and enhance the experience of their consumer and business customers alike, thus making it a critical tool for today’s financial landscape. The key is integrating these capabilities into today’s infrastructure to maximize impact and efficiency.
Why Now?
With the rapid digital transformation in financial services, the need for efficient, AI-powered solutions is more pressing than ever. Gen AI can significantly improve developer efficiency, automate job functions, and boost overall business operations. According to McKinsey, AI could lead to a 40% increase in developer efficiency by 2025 and replace 85 million global jobs in the same period.
Who Cares?
- Financial institutions
- FinTech startups
- Payment processors
- Lending platforms
What Areas Excite Us Today?
Front-end Solutions
- AI-enabled lead gen optimization (e.g. lead to agent matching, automated onboarding communication etc.)
- Personalized and dynamic product marketing (e.g. organic, tailored card or mortgage presentment in mobile app)
- Sales Co-Pilots for the “front line” of financial services (e.g. business bankers in branches, field insurance agents, outbound RIAs)
Back-end Solutions
- Automating mundane (yet detail-oriented) work activities and streamlining broader finance and accounting functions
- Training AI on existing topologies to automate systems integrations, identify improvements (and implement them)
- Enhancing compliance monitoring, credit assessment, and personalization across the customer lifecycle
- Enabling continuous monitoring and improvement in customer service interactions; pushing poor manual or electronic customer experiences (e.g. IVRs) to human-realistic virtual agents
Key Determinants of Success
The most successful AI implementations will offer easy integration and significant impact with low friction, leading to high adoption rates and meaningful results.
Generative AI for Retail
Retailers and brands are swiftly adopting Generative AI to streamline operations, enhance customer experiences, and create new revenue streams. Unlike past tech trends, Gen AI adoption in retail is both fast and meaningful, offering disruptive capabilities that go beyond incremental improvements.
Why Now?
The retail landscape is shifting with an influx of new AI technologies that can drive significant operational efficiencies and create unique value propositions. Categories such as copy creation and visual asset generation are already seeing widespread adoption, while more disruptive uses like AI-native marketing and AI-powered search will take longer, but may have more lasting effects.
Who Cares?
- Retail brands
- E-commerce platforms
- Marketing agencies
- Supply chain managers
What Areas Excite Us Today?
Emerging Use Cases
- Trend Identification & Product Development: Using AI to identify trends and aid in product design.
- Sourcing, Procurement, and Negotiation: Platforms that autonomously handle supply chain negotiations.
- Customer Service: AI-driven chatbots and conversational platforms to improve service and reduce costs.
- Marketing Tech: AI-native platforms for SMS and email marketing.
- Copy and Content Creation: Tools for automating marketing copy and product descriptions.
- Image/Video Creation: Automated tools for generating marketing visuals.
- E-Commerce Search: Enabling customers to find products using AI instead keyword searches.
- Business Intelligence: AI-driven tools to make data more accessible.
- Personalization & Optimization: AI-generated personalized customer experiences.
Key Determinants of Success
Success in retail AI will depend on the ability to deliver high-impact solutions that are easy to adopt and integrate into existing systems, ultimately leading to enhanced customer experiences and operational efficiencies.
01 — Tokenizing Value: Stablecoins
Programmable Dollars for Borderless B2B Payments
Stablecoins offer a faster, cheaper, and programmable alternative to legacy cross-border payments. They’re already transforming B2B flows, treasury ops, and global merchant settlement.
02 — Agentic Commerce
AI Is Changing How Consumers Find (and Buy) Products and Services
AI is reshaping how people discover and buy online. As bots replace browsers, merchants and infrastructure providers must adapt to a world where shopping happens via API, not UI.
03 — AI for Accounting
AI will Automate Many Core Finance Functions
AI is already automating many tasks for finance teams. As the technology advances, its applicability will expand to support broader workflows across accounting and auditing.
04 — Commercial Lending
Modernizing the Credit Stack for Banks & Private Credit
Commercial credit is shifting fast, but the systems that support it haven’t kept up. As private credit steals increasing share from bank lenders, tech is the key to faster decisions, smarter risk, and better margins.