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Why AI Product Roadmaps Still Fail at Scale in Financial Services in 2026

Hamza Qamar

Most AI product roadmaps in financial services fail not because of weak models, but because no one owns decisions, controls, or outcomes. In 2026, AI is forcing organisations to confront what must remain deterministic, where probabilistic reasoning is safe, and how governance operates inside products, not outside them. Hamza Qamar, Senior Director of Product, Innovation & Design, explains why busy AI roadmaps deliver little impact, how decision systems differ from features, and what product leaders must own to scale AI responsibly. In this article, he offers a practical framework for designing AI products that are operable, auditable, and accountable in regulated environments.

10 Telecom Trends Shaping AI-Assisted Modernization in 2026 and Beyond

Naresh Babu

Telecom is entering a period where rising expectations for real-time, intelligent connectivity are colliding with the limits of legacy OSS/BSS, manual testing, and siloed operations. As AI shifts from basic automation to true AI-assisted engineering, operators now have a path to modernize faster, safer, and with greater precision. In this article, Naresh Babu, AI Technology Leader and Digital Transformation Specialist, explores that shift and outlines the ten trends shaping AI-assisted modernization in 2026 and beyond, from autonomous networks and composable IT to AI-enhanced CX, cloud-edge convergence, and workforce transformation. In it, he also lays down the clear business impact of AI-assisted modernization for the telco industry, and guidance for telecom leaders preparing for the next wave of modernization.
2026 Trends Guiding Financial Services Out of AI Pilot Purgatory

2026 Trends Guiding Financial Services Out of AI Pilot Purgatory

Praveen Kumar

2025 was the year of experimentation in financial services. when generative and agentic AI dominated conversations, but not balance sheets. In 2026, that changes. Financial leaders face a new era of accountability: one where data governance, real-time visibility, and regulatory readiness define the winners. In this article, Praveen Kumar, Practice Lead, Data & AI, outlines the key trends forming a practical roadmap for responsible, scalable AI adoption in the financial sector, turning AI from a promising idea into an operational discipline that drives measurable trust, compliance, and ROI.

2026 Trends Shaping How Financial Institutions Modernize with AI-Assisted Engineering

Naresh Babu

As financial institutions race to modernize aging systems, a new wave of 2026 trends is reshaping how transformation happens. AI-assisted engineering is emerging as the cornerstone of modernization, accelerating code remediation, automating testing, and embedding compliance across the software lifecycle. Whether it’s modernizing legacy systems, automating testing, or generating living documentation, an AI-powered approach helps financial institutions move faster, safer, and smarter; turning modernization from a roadmap into measurable progress. In this article, Naresh Babu, AI Technology Leader and Digital Technology Specialist, explores the key trends driving that shift, how AI is bridging the legacy-modern gap, and what forward-thinking banks and insurers are doing today to stay ahead of the curve in 2026.

2026 Trends Redefining How Financial Services Build AI Products For Measurable ROI

Hamza Qamar

AI in financial services is shifting from experimentation to execution. 2026 will mark the year when product leaders move from pilots to profit, embedding AI, data, and governance directly into customer journeys. In this article, Hamza Qamar, Senior Director of Product, Innovation and Design, explores the defining trends driving that transformation, from cloud-smart modernization to compliance-as-code. Learn how financial institutions are building AI products that deliver measurable impact, faster releases, and lasting trust across every line of business, with real use cases, implementation steps, and the AI risks to watch out for in 2026.

Designing Transparent AI That Wins Telecom Loyalty

Laura McCutchan

AI is embedded in nearly every telecom customer interaction, yet adoption and trust remain fragile when decisions feel opaque. In this article, Laura McCutchan, Director of Design, outlines how transparent AI interface design can transform that “black box” into a trusted asset. She introduces four pillars, Explainability, Control, Consistency, and Ethical Design, and shows how they reduce churn, boost loyalty, and ensure compliance with regulations like the EU AI Act. With real-world telecom examples, the article highlights how design leaders can embed transparency without sacrificing privacy or security, turning trust into a measurable business advantage for both customers and internal teams.

How Agentic AI is Unlocking New Revenue Opportunities for Telecom

Hamza Qamar

As telecom operators face stagnant ARPU and shrinking margins, Agentic AI offers a smarter path to monetization. In this article, Hamza Qamar, Senior Director of Product and Design, explores how autonomous AI agents can drive real-time bundling, monetize micro-moments, and automate loyalty and credit actions, unlocking new revenue streams with minimal human intervention. It outlines four high-impact use cases, as well as a case study showing a 30% reduction in churn. You will also get a phased roadmap for scaling agentic systems across BSS and customer channels. With measurable business impact and built-in governance guidance, this article offers strategics that help telcos move from reactive campaigns to proactive, intelligent monetization at scale.

Overcoming AI Regulation Complexities with Robust Governance Frameworks

Naresh Babu

The financial sector is rapidly embracing Artificial Intelligence (AI), with GenAI leading a wave of transformation. But while this opportunity is substantial, so are the risks. Generative AI introduces new challenges around data privacy, algorithmic bias, legal liability, and cyber threats. Current governance models are often unprepared to manage the complexity and scale of these technologies. Drawing on real-world case studies from JPMorgan, Wells Fargo, and others, Naresh Babu, AI Technology Leader and Digital Transformation Specialist, provides practical steps to operationalize risk management, strengthen oversight, and leverage robust AI governance frameworks to turn AI from a high-risk experiment into a powerful engine for growth and competitive advantage.

Modern Data Strategy to Transform Chaos into Growth

Praveen Kumar

Financial institutions face increasing regulatory pressure and rising customer expectations. This has given rise to a pressing need within the financial services industry to modernize data. Anchored in governance, quality, security, and alignment, a modern data strategy helps unlock trusted insights, enable AI adoption, and ensure regulatory compliance at scale. Praveen Kumar, Practice Leader Data & AI, explores how to modernize your data strategy through four practical phases, aligned with emerging trends and embedded in solving data complexities to gain a competitive edge and generate business impact.

Double Your ROI with a 4-Phased Human-Centred Design Playbook

Laura McCutchan

As digital disruption intensifies and customer expectations rise, financial services leaders are under pressure to deliver intuitive, consistent, and high-value experiences across all touchpoints. In this article, Laura McCutchan, Director of Design, explores how human-centered design (HCD) can be a powerful lever for innovation and growth, enabling banks and insurers to embed empathy, cross-functional collaboration, and data-driven decision-making into every strategic initiative. Grounded in insights from real-world consulting experience, the article introduces a 4-phase HCD playbook tailored to help financial institutions unlock ROI, build trust, and accelerate innovation cycles. It also highlights the transformative role of AI when combined with ethical, user-centric design, and presents practical strategies for upskilling design teams to thrive in AI-augmented environments.
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