AI Banking Platform Strategy: Streamline Customer Experiences (2026)
AI Banking Platform Strategy: Streamline Customer Experiences (2026)
Artificial Intelligence
Dec 12, 2025


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A platform approach modernizes AI banking by unifying the engagement layer and integrating journeys end-to-end. As Backbase’s Jouk Pleiter argues, banks that platformize their customer experience can embed AI where it matters—decision-making, personalization, and service—scaling value faster than channel-by-channel experiments. This is how established banks regain speed and relevance.
Executive argument: the platform is the product
Banks don’t win AI-era loyalty by attaching tools to outdated systems. They win by treating the platform itself as the product—a vertically integrated engagement layer that manages every sales and servicing journey, front-to-back, with AI woven in. That’s the core of Jouk Pleiter’s argument: platform thinking breaks down silos, standardizes journeys, and creates control points where AI can add real value without disrupting the system.
The strategic shift is twofold. First, modernize the engagement layer—the point where customers actually engage with your bank—so journeys are managed end-to-end rather than by channels or products. Second, add an “intelligence fabric” to that platform so AI enhances each step: onboarding, service, advice, fraud, collections. This is how established banks regain speed without continuous core replacement projects.
Why now: AI has changed the economics of modernization
In 2026, AI is not an add-on; it’s the new operating system of growth and cost-to-serve. Banks that scale AI do three things differently: connect use-cases to value, standardize a capability stack (data, models, orchestration), and encourage adoption with new ways of working. That blueprint benefits platforms that centralize orchestration and reuse across journeys—rather than one-off pilots in scattered channels.
Market signals support this: vendors are providing AI-powered engagement platforms and partnerships to bridge the human-digital gap (e.g., Backbase’s AI-powered platform and Unblu integration), while major banks are deploying generative AI into frontline experiences on a large scale (e.g., NatWest). The direction is clear: platformize, then productize AI across journeys.
What a platform approach looks like (and what it isn’t)
A true platform is journey-based and progressive: select a priority journey—say SME onboarding—and modernize it front-to-back, reusing components across segments. It avoids “rip-and-replace” doctrine, but also avoids the opposite trap: incremental tinkering that never transforms customer experience. Composability is important, but without a unifying engagement layer, composability devolves into integration theatre.
Backbase’s approach is instructive: an engagement platform that unifies journeys and provides standard control points for AI—decision-making, personalization, and agentic workflow—rather than spreading point bots across channels. The goal is a bank-owned platform where AI can be governed, audited, and updated quickly.
Leadership playbook: five choices that separate winners
Own the engagement layer. Make it your main product. Your channels are simply interfaces; the journey logic and data live on the platform. This is how you deliver improvements weekly, not yearly. backbase.com
Adopt journey-based modernization. Fund by outcome (e.g., “Reduce onboarding abandonment 30%”), not by system. Reuse components across retail, SME, and wealth. backbase.com
Establish an intelligence fabric. Centralize retrieval, models, and agent orchestration so AI is permissioned, explainable, and reusable across journeys. McKinsey & Company
Design for human-digital collaboration. Integrate automation with guided conversations—think co-browsing, secure chat, and AI assistants that escalate to humans seamlessly. FF News | Fintech Finance
Govern for scale. Treat prompts, policies, and metrics as product artifacts. Measure conversion, time-to-resolution, fraud catch-rate, and NPS by journey, not channel. McKinsey & Company
What great looks like: signals of maturity in 2026
Unified customer journeys across sales and service, with shared components and release schedules.
AI agents in production handling specific tasks (pre-fill, triage, collections nudges) with human-in-the-loop controls.
Design-ops for journeys, not pages: versioned flows, experiment frameworks, and telemetry that foster continuous improvement.
Vendor ecosystem as a feature, not a dependency: targeted partnerships to close gaps without losing platform control.
FAQs
Q1: How does the platform approach benefit banks?
It treats the engagement layer as a product, standardizing journeys and creating governed touchpoints for AI. The result: faster change cycles, higher conversion, and lower cost-to-serve compared to channel-led projects. McKinsey & Company
Q2: What role does AI play in this approach?
AI is integrated into the platform’s “intelligence fabric”, powering personalization, decision-making, and agentic workflow that can be reused across journeys—rather than being scattered in each channel. backbase.com
Q3: Why is modernization urgent now?
Competitive advantage is shifting to banks that can deploy AI effectively. Platformization shortens time-to-value and reduces integration challenges, allowing established banks to match the speed of digital-native entities. BCG Global
Sources:
McKinsey interview with Jouk Pleiter on the platform approach. McKinsey & Company
Backbase AI-powered Banking Platform and Intelligence Fabric. backbase.com
How to modernize the engagement layer (Backbase podcast with Pleiter). backbase.com
Journey-based progressive modernization explainer. backbase.com
AI at scale in banking (McKinsey blueprint). McKinsey & Company
BCG on the AI reckoning for banks (strategy context). BCG Global
Backbase–Unblu partnership (human-digital collaboration). FF News | Fintech Finance
Next Steps
Ready to platformize your engagement layer and deliver AI-powered journeys in months, not years? Generation Digital can help you prioritize the first journeys, establish the intelligence fabric, and create the operating model that sustains it.
A platform approach modernizes AI banking by unifying the engagement layer and integrating journeys end-to-end. As Backbase’s Jouk Pleiter argues, banks that platformize their customer experience can embed AI where it matters—decision-making, personalization, and service—scaling value faster than channel-by-channel experiments. This is how established banks regain speed and relevance.
Executive argument: the platform is the product
Banks don’t win AI-era loyalty by attaching tools to outdated systems. They win by treating the platform itself as the product—a vertically integrated engagement layer that manages every sales and servicing journey, front-to-back, with AI woven in. That’s the core of Jouk Pleiter’s argument: platform thinking breaks down silos, standardizes journeys, and creates control points where AI can add real value without disrupting the system.
The strategic shift is twofold. First, modernize the engagement layer—the point where customers actually engage with your bank—so journeys are managed end-to-end rather than by channels or products. Second, add an “intelligence fabric” to that platform so AI enhances each step: onboarding, service, advice, fraud, collections. This is how established banks regain speed without continuous core replacement projects.
Why now: AI has changed the economics of modernization
In 2026, AI is not an add-on; it’s the new operating system of growth and cost-to-serve. Banks that scale AI do three things differently: connect use-cases to value, standardize a capability stack (data, models, orchestration), and encourage adoption with new ways of working. That blueprint benefits platforms that centralize orchestration and reuse across journeys—rather than one-off pilots in scattered channels.
Market signals support this: vendors are providing AI-powered engagement platforms and partnerships to bridge the human-digital gap (e.g., Backbase’s AI-powered platform and Unblu integration), while major banks are deploying generative AI into frontline experiences on a large scale (e.g., NatWest). The direction is clear: platformize, then productize AI across journeys.
What a platform approach looks like (and what it isn’t)
A true platform is journey-based and progressive: select a priority journey—say SME onboarding—and modernize it front-to-back, reusing components across segments. It avoids “rip-and-replace” doctrine, but also avoids the opposite trap: incremental tinkering that never transforms customer experience. Composability is important, but without a unifying engagement layer, composability devolves into integration theatre.
Backbase’s approach is instructive: an engagement platform that unifies journeys and provides standard control points for AI—decision-making, personalization, and agentic workflow—rather than spreading point bots across channels. The goal is a bank-owned platform where AI can be governed, audited, and updated quickly.
Leadership playbook: five choices that separate winners
Own the engagement layer. Make it your main product. Your channels are simply interfaces; the journey logic and data live on the platform. This is how you deliver improvements weekly, not yearly. backbase.com
Adopt journey-based modernization. Fund by outcome (e.g., “Reduce onboarding abandonment 30%”), not by system. Reuse components across retail, SME, and wealth. backbase.com
Establish an intelligence fabric. Centralize retrieval, models, and agent orchestration so AI is permissioned, explainable, and reusable across journeys. McKinsey & Company
Design for human-digital collaboration. Integrate automation with guided conversations—think co-browsing, secure chat, and AI assistants that escalate to humans seamlessly. FF News | Fintech Finance
Govern for scale. Treat prompts, policies, and metrics as product artifacts. Measure conversion, time-to-resolution, fraud catch-rate, and NPS by journey, not channel. McKinsey & Company
What great looks like: signals of maturity in 2026
Unified customer journeys across sales and service, with shared components and release schedules.
AI agents in production handling specific tasks (pre-fill, triage, collections nudges) with human-in-the-loop controls.
Design-ops for journeys, not pages: versioned flows, experiment frameworks, and telemetry that foster continuous improvement.
Vendor ecosystem as a feature, not a dependency: targeted partnerships to close gaps without losing platform control.
FAQs
Q1: How does the platform approach benefit banks?
It treats the engagement layer as a product, standardizing journeys and creating governed touchpoints for AI. The result: faster change cycles, higher conversion, and lower cost-to-serve compared to channel-led projects. McKinsey & Company
Q2: What role does AI play in this approach?
AI is integrated into the platform’s “intelligence fabric”, powering personalization, decision-making, and agentic workflow that can be reused across journeys—rather than being scattered in each channel. backbase.com
Q3: Why is modernization urgent now?
Competitive advantage is shifting to banks that can deploy AI effectively. Platformization shortens time-to-value and reduces integration challenges, allowing established banks to match the speed of digital-native entities. BCG Global
Sources:
McKinsey interview with Jouk Pleiter on the platform approach. McKinsey & Company
Backbase AI-powered Banking Platform and Intelligence Fabric. backbase.com
How to modernize the engagement layer (Backbase podcast with Pleiter). backbase.com
Journey-based progressive modernization explainer. backbase.com
AI at scale in banking (McKinsey blueprint). McKinsey & Company
BCG on the AI reckoning for banks (strategy context). BCG Global
Backbase–Unblu partnership (human-digital collaboration). FF News | Fintech Finance
Next Steps
Ready to platformize your engagement layer and deliver AI-powered journeys in months, not years? Generation Digital can help you prioritize the first journeys, establish the intelligence fabric, and create the operating model that sustains it.
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