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Data, AI, And Analytics Leaders

Drive Growth Through Trusted AI Insights

Delivering AI-powered insights that drive business growth requires a comprehensive strategy that aligns data, technology, and business leaders. To be successful, these leaders must find ways to expand their organizational influence, build trust in their work, and enable the business to make better decisions.

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Challenges You Face

Today’s data, AI, and analytics leaders often struggle to drive significant business impact because their role and function may not be clearly defined, limiting their influence across their organization. Forrester can help address these and other significant challenges, including:

  • Overcoming organizational silos to align business units and functions around data and AI.
  • Implementing data governance effectively.
  • Defining career development tracks to retain skilled data, AI, and analytics professionals.
  • Balancing emerging technology and innovation with practical goals and implementation.
  • Clearly defining your role and responsibilities to avoid overlap with other positions.

How Forrester Helps You Drive Business Results

Forrester empowers data, AI, and analytics leaders to build and implement strategies that will scale data and AI efforts and align your organization around a data-driven culture.

Bold Solutions Fit For You

Forrester helps data, AI, and analytics leaders and their teams deliver consistent data strategies that align to business goals while embracing the future of data and AI with clarity and confidence.

Create Business Value From Trusted Data And AI

Forrester Decisions for Data, AI & Analytics helps enterprise data and technology leaders create business value from trusted data, build the foundation to scale AI, and cultivate a data-driven culture with urgency.

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Blog

In The AI Era, Banks Need Dynamic Platforms — Results From The Forrester Wave™: Digital Banking Engagement Platforms, Q2 2026

Peter Wannemacher 1 day ago
To compete for customers and grow profitably, banks need the ability to adjust as much and as fast as required at any given moment. Leading digital banking engagement platforms (DBEPs) make that possible. My new report, The Forrester Wave™: Digital Banking Engagement Platforms, Q2 2026, reveals insights about the current AI and technology landscape in […]
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Blog

How AI Is Rearchitecting Lending

Zhi Ying Barry 2 days ago
Lending Is Reaching An Inflection Point More than 80% of financial services (FS) AI decision‑makers plan to increase investments in both predictive AI and generative AI (genAI), with most firms expecting double‑digit growth. The immediate focus for the majority of FS leaders remains pragmatic: scaling origination, reducing friction caused by handoffs, and improving risk control. […]
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Blog

Salesforce’s New AgentExchange Store: Easier AI Helpers But Still Inside Their Walled Garden

Faram Medhora 5 days ago
Salesforce’s reimagined marketplace makes buying AI and applications inside Salesforce dramatically easier and makes leaving Salesforce later even harder. Salesforce has merged three separate “stores” for apps and AI tools into a single marketplace called AgentExchange. It is live now with roughly 13,000-plus ready-made apps, AI agents, and automation components. The stated goal is simple: […]
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Blog

Tech Leaders, Brace Yourselves: AI Costs Will Only Go Up

Greg Zorella 5 days ago
Anthropic gave leaders a blunt signal about planning for LLM charges when it introduced blended pricing for enterprise users of Claude recently. Enterprises with over 150 seatholders will now pay a blanket per-seat charge ($20 per seat at the moment), plus a variable charge based on API usage and which Claude model they’re using. When […]
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Blog

Beyond Chatbots: Designing Conversational Banking Experiences That Scale

Aurelie L'Hostis 5 days ago
Learn how banks can scale conversational experiences at CX Summit EMEA 2026.
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Blog

Introducing Forrester’s AI Model Openness Framework

Mike Gualtieri April 17, 2026
Forrester’s Model Openness Framework can help you assess the real degree of openness in any AI model, whether it’s labeled open source or commercial, across three key dimensions: reproducibility, usage rights, and community momentum.
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