Latest news with #Dataiku
Techday NZ
11-07-2025
- Business
- Techday NZ
The next frontier of AI product development: building systems that learn with your users
In 2025, Amazon rolled out an adaptive AI upgrade for Alexa (Alexa Plus) that instantly incorporated live user feedback to adjust tone, clarify responses, and even change recommended actions on the fly. Overnight, Alexa went from a passive voice assistant to an evolving partner that felt more human, one that adapts as you do. This isn't just an incremental improvement. It's a glimpse of what's next for AI systems across industries. The past decade has seen AI reshape everything from recommendation engines to customer service scripts. But most models we rely on today are static, trained once on historical data and then frozen in time. They might receive updates periodically, but they don't truly grow with us. That's where adaptive AI steps in: systems designed to learn continuously, in real time, directly from users. Why Adaptive AI is the Future Adaptive AI refers to systems that adjust behavior and outputs based on ongoing feedback, rather than waiting for scheduled retraining cycles. Instead of simply automating old patterns, adaptive AI systems co-create new solutions alongside their users. According to McKinsey, while 40% of organizations are experimenting with AI, very few are using it to empower human adaptability and creativity at scale. Most current use cases still focus on automating routine tasks rather than elevating human decision-making or improving responsiveness. As highlighted in Dataiku's 2025 GenAI Trends report, user-centric adaptive AI is becoming a strategic differentiator. Systems that adapt in real time don't just execute tasks; they learn preferences, anticipate needs, and build trust. The Power of Feedback Loops A key ingredient in adaptive AI is the feedback loop. Whether it's explicit (a thumbs-up or comment) or implicit (scrolling behavior, click hesitation), these signals help systems evolve to serve users better. Take Spotify as an example: every skip, replay, or playlist addition feeds its adaptive recommendation algorithms. The more you interact, the more it personalizes your experience, creating a sticky, almost addictive relationship with the product. Dataiku emphasizes that involving users in shaping AI outputs is essential for adoption and trust. Products that visibly improve in response to user behavior drive higher engagement and loyalty. This continuous loop – learn, adapt, improve – forms the core of adaptive AI. Challenges to Overcome While the promise is huge, adaptive AI presents real challenges. First and foremost: data privacy. Continuous learning requires ongoing data collection, and companies must be transparent and rigorous about how data is used. Compliance with global regulations like GDPR and forthcoming AI-specific frameworks isn't optional – it's foundational. Another critical challenge is stability. A system that overreacts to every micro feedback can create inconsistent or even chaotic user experiences. Striking a balance between adaptability and reliability is key. Design guardrails and thorough monitoring become crucial to avoid model drift or unexpected behaviors that erode trust. On the infrastructure side, adaptive AI demands real-time processing and ultra-low-latency architectures. Many legacy systems simply aren't built for this. Transitioning to adaptive AI often means rethinking entire data pipelines, backend architectures, and user interfaces, an investment not every organization is ready to make. Beyond Automation: AI as a Partner Perhaps the most exciting shift adaptive AI offers is transforming AI from a tool into a partner. Instead of simply automating tasks, adaptive AI augments human capabilities, helping teams make better decisions and solve problems creatively. McKinsey describes this evolution as the rise of "superagency", empowering employees to move from repetitive work to strategic and creative contributions, supported by adaptive AI systems. For example, customer service agents using AI that not only suggests responses but also learns and evolves with every interaction can focus more on empathy and complex problem-solving. Prediction: The Real Game-Changer While automation and personalization are valuable, predictive capabilities are where adaptive AI truly shines. Systems that can forecast churn, anticipate supply chain disruptions, or warn of potential payment failures enable businesses to act before issues escalate. But prediction without transparency can lead to blind trust or overreliance. As models grow more sophisticated, explaining decisions and keeping humans in the loop remain essential. Advice for Builders and Leaders For founders and tech leaders looking to tap into adaptive AI, my advice is simple: start small and iterate fast. Pilot feedback loops in non-critical parts of your product to understand user responses and system behavior. Invest early in ethical and compliance frameworks, these aren't afterthoughts but core to building long-term trust. Build cross-functional teams that include data scientists, product managers, UX researchers, and compliance experts. Finally, remember: the most successful AI products of the future won't just be fast or accurate. They'll feel like true partners – systems that evolve with your users, build loyalty, and create real business value over time.
Yahoo
25-06-2025
- Business
- Yahoo
Dataiku Joins HPE Unleash AI Ecosystem to Accelerate Enterprise AI
The Universal AI Platform™ integrates with HPE's AI-optimized infrastructure to deliver fully governed, production-ready agentic AI systems NEW YORK & LAS VEGAS, June 25, 2025 (GLOBE NEWSWIRE) -- Dataiku, the Universal AI Platform™, today announced it has joined the HPE Unleash AI partner program, bringing together enterprise-ready AI orchestration and trusted infrastructure to accelerate the deployment and adoption of generative and agentic AI. With this collaboration, organizations gain a clear path to move beyond experimentation and deliver production-ready AI with the required speed, confidence, and governance to meet corporate goals and standards, without compromise. Dataiku's participation in the Unleash AI partner program is a joint commitment to enable enterprises to deploy generative, agentic, and physical AI at scale. The Universal AI Platform from Dataiku gives organizations the tools to create, connect, and control AI agents across varied business types, tech stacks, and use cases. Paired with HPE's AI-optimized infrastructure and NVIDIA's industry-specific AI Blueprints, Dataiku provides a clear path to deploying AI that drives measurable results across sectors. 'The challenge for enterprises isn't just building AI agents and GenAI apps—it's controlling how they behave, evolve, interact, and create value in the real world. Dataiku is uniquely positioned to deliver this combination of AI creation, connection, and control at enterprise scale,' said David Tharp, SVP of Partnerships at Dataiku. 'Through our work with HPE, we're enabling organizations to confidently operationalize GenAI and agentic systems with the guardrails, governance, and flexibility needed to align with enterprise standards from day one.' A Unified Foundation for Enterprise AI Innovation The alliance brings together everything enterprises need to run AI, from development and orchestration to deployment and monitoring—all in one integrated stack that is accelerated by NVIDIA Enterprise AI Factory validated design. The core foundation is formed by HPE Private Cloud AI, which is strengthened by NVIDIA-Certified Systems from HPE, like NVIDIA RTX PRO Server and NVIDIA HGX B200. As a featured agentic AI platform partner in the Unleash AI ecosystem, Dataiku enables customers to: Rapidly build and deploy generative and agentic applications. Leverage the pre-built NVIDIA AI-Q Blueprint and NVIDIA NIM microservices for copilots, digital humans, and knowledge agents. Orchestrate end-to-end AI workflows in a governed, collaborative environment. Deploy with enterprise-grade performance, security, and scalability. AI Designed for Real Business Outcomes Today, The Universal AI Platform from Dataiku is trusted by 1 in 4 of the world's top companies, based on the top 500 of the 2024 Forbes Global 2000 list (excluding China). Customers across multiple industries, including financial services, life sciences and healthcare, retail, energy, marketing, and manufacturing are achieving measurable AI outcomes with Dataiku, from optimizing processes for productivity gains to augmenting employee decision-making to transforming their business models with entirely new revenue streams. Through the HPE Unleash AI program, Dataiku customers also gain access to powerful enablement resources, such as technical workshops, joint support, and co-innovation opportunities to accelerate adoption while reducing complexity and risk. Together, Dataiku and HPE enable faster deployment, better collaboration between technical and business teams, built-in governance and transparency, and more efficient use of compute resources—all while keeping enterprise AI costs predictable and agentic systems under tight control. For more information on Dataiku's participation in the HPE Unleash AI partner program, visit: For more information on the Dataiku partner ecosystem, visit: About Dataiku Dataiku is The Universal AI Platform™, giving organizations control over their AI talent, processes, and technologies to unleash the creation of analytics, models, and agents. Agnostic by design, it integrates with all clouds, data platforms, AI services, and legacy systems to ensure full technology optionality — empowering customers to future-proof their AI initiatives. With built-in governance and no-, low-, and full-code capabilities, Dataiku enables the world's largest companies to confidently build and manage differentiated AI that drives measurable business value. Dataiku has over 1,100 employees across 13 offices worldwide, serves over 700 enterprise customers, and is backed by investors, including Wellington Management, Battery, CapitalG, ICONIQ, and FirstMark. For more, visit the Dataiku blog, LinkedIn, X, and YouTube. ###CONTACT: Kevin McLaughlin Dataiku press@ in retrieving data Sign in to access your portfolio Error in retrieving data Error in retrieving data Error in retrieving data Error in retrieving data
Forbes
18-06-2025
- Business
- Forbes
For CEOs, AI Innovation Is Now A Near-Term Survival Requirement
AI requires a shift in mindset for the C-Suite. Companies that fail to adopt AI technologies risk falling behind their competitors, losing market relevance, and even jeopardizing their long-term survival. 'AI is no longer a long-term innovation initiative—it's a near-term survival requirement.' This is according to a recently published Harris Poll survey conducted on behalf of AI company Dataiku, which says 74% of CEOs overall, and 79% in the U.S., said they could lose their jobs within two years if they don't deliver measurable AI-driven business gains. So, why is AI innovation a 'near-term survival requirement?' In a nutshell, AI requires a shift in mindset for the C-Suite. Companies that fail to adopt AI technologies risk falling behind their competitors, losing market relevance, and even jeopardizing their long-term survival—an ominous situation for any chief executive. So, rather than considering the risks of implementing AI projects, CEOs should weigh the costs of inaction. One of the most immediate and significant risks of not adopting AI is the potential loss of a competitive edge. Companies that are leveraging AI to improve efficiency, enhance customer experiences, and innovate are gaining a distinct advantage over those that remain hesitant. For instance, AI-powered tools can optimize supply chains, automate routine tasks, and generate insights from big data, leading to faster decision-making, improved profitability, and the ability to innovate more quickly than competitors. Failing to adopt AI means that competitors who are embracing the technology will likely outpace your organization, attracting more customers, increasing market share, and outperforming you in critical areas such as product development, personalization, and operational efficiency. AI isn't just about improving existing processes; it's about enabling new ways of thinking and unlocking new opportunities. The technology has the potential to improve customer service, speed product development, and more. Companies that delay adopting AI risk missing out on innovative solutions that could fundamentally transform or accelerate their businesses. For example, AI can facilitate breakthroughs in product design by enabling rapid prototyping and simulations. It can also drive innovation in marketing by offering hyper-targeted campaigns powered by machine learning. CEOs who hesitate to implement AI may find their organizations stuck in traditional ways of thinking while competitors race ahead with cutting-edge innovations. AI inaction can lead to inefficiency and rising operational costs. AI has the potential to automate many time-consuming and repetitive tasks, freeing up valuable human resources for more strategic work. Tasks such as data entry, report generation, customer service inquiries, and supply chain management can be optimized using AI, reducing the time and costs associated with manual labor. Without AI, organizations may find themselves running inefficient processes, which could lead to higher operational costs and less effective resource allocation. Companies that resist AI may find their cost structures out of synch with the market, widening the competitive gap. Customers today have higher expectations than ever before. AI-powered tools can provide hyper-personalized experiences, faster response times, and enhanced customer support through chatbots and virtual assistants—not the binary phone trees of yesterday, but personalized, human-like agents that can accomplish tasks on your behalf. Businesses that fail to implement AI risk disappointing customers with outdated systems, slow service, and generic experiences that no longer meet modern standards. This is happening today. Companies that do not invest in AI may lose customer loyalty to competitors that offer more sophisticated, AI-driven experiences. Declines in customer satisfaction are a one-way street to reduced revenue and brand perception. Data is one of the most valuable assets businesses possess, yet many organizations fail to capitalize on this asset. AI excels at extracting valuable insights from vast amounts of data, enabling businesses to make data-driven decisions that can improve performance and mitigate risks. Companies that don't implement AI solutions risk leaving vast amounts of data untapped, missing out on opportunities to enhance decision-making, predict trends, and gain deeper insights into customer behavior. Data-driven strategies powered by AI can inform everything from product development to customer engagement, and companies that do not embrace these tools risk making decisions based on outdated or incomplete information. As AI becomes more integrated into business operations, attracting and retaining top talent in fields like data science, machine learning, and AI engineering will become increasingly important. Organizations that fail to prioritize AI may struggle to attract highly skilled employees, as the best talent often seeks out companies that are on the cutting edge of technology. On top of that, your existing employees may become frustrated with the lack of advancement AI can unlock. Talented workers want to work for companies that embrace innovation. Companies that avoid AI may find themselves with an outdated workforce and an inability to attract the next generation of top-tier talent. AI is rapidly becoming a competitive advantage in regulatory-heavy industries such as healthcare, finance, and retail. Businesses that fail to implement AI solutions may be missing an opportunity to streamline or automate compliance, especially when it comes to data protection, fraud detection, and risk management. For example, AI can enhance cybersecurity, identify financial fraud, and detect irregularities in transactions or operations. Failing to adopt AI for compliance purposes can leave an organization vulnerable to breaches, non-compliance penalties, and reputational damage. Industries across the globe are experiencing rapid disruption due to AI-powered companies challenging traditional business models. From fintech startups leveraging AI for financial services to retail giants using machine learning for inventory management and customer insights, businesses that fail to adapt to this new environment risk being left behind as more innovative competitors take the field. By taking a more cautious AI stance, companies open themselves up to the risk of disruption from more nimble, tech-savvy competitors who are better able to respond to market changes and evolving customer expectations. Again, CEOs don't want to be on the wrong end of the innovation curve. Failing to adopt AI can damage an organization's reputation as a forward-thinking, innovative brand. Customers, employees, and investors expect companies to stay ahead of the competition by taking advantage of technological trends. Those that fail to do so may be seen as a tired, old brand from yesterday. Younger consumers and employees are more likely to evaluate brands based on their adoption of newer technologies and ability to innovate. Aversion to AI and newer tech could signal a company that is not keeping up. No brand wants to be seen as tired. The risks associated with inaction are considerable, and the risks of survival are real. Whether it's customer experience, data-driven insights, regulatory compliance, or brand perception, AI provides measurable performance characteristics, and CEOs with losing formulas may not be CEOs very long. But that also doesn't mean chiefs need to dive headfirst into the deep end. It's important to learn and adapt. Think about low-hanging fruit in your organization. Small projects that can be automated. How old is your call center solution, for example? Where are there opportunities to drive new revenue by understanding customer preferences and buying patterns? By choosing bite-sized projects that yield real improvements, CEOs will not only learn but also take essential steps to improve their business metrics.
Tahawul Tech
16-06-2025
- Business
- Tahawul Tech
Dataiku launches new FSI Blueprint designed to accelerate Agentic AI in financial services
Dataiku, the Universal AI Platform™ has announced a new FSI Blueprint for deploying agentic AI systems in financial services. This blueprint is designed to help banking and insurance institutions create, connect, and control intelligent AI agents at scale—with the governance, performance, and flexibility required for production in these highly regulated industries. This announcement builds on Dataiku's integration in the NVIDIA Enterprise AI Factory validated design, which helps enterprises accelerate the development and deployment of secure, scalable AI infrastructure. 'AI agents represent the next major shift in enterprise productivity, and banks are among the earliest adopters,' said Malcolm deMayo, Vice President of Global Financial Services at NVIDIA. 'This new bank blueprint from Dataiku, accelerated by NVIDIA, combines reusable components that enable banks to automate thousands of repetitive manual tasks. This allows institutions to deploy intelligent systems that can adapt to complex workflows and evolve responsibly over time—all while meeting regulatory and compliance requirements through central governance.' The FSI Blueprint combines The Universal AI Platform and Dataiku LLM Mesh with NVIDIA NIMmicroservices, NVIDIA NeMo, and GPU-accelerated infrastructure. It leverages AI agents powered by NVIDIA to provide financial institutions with a secure and modular foundation for building agentic AI solutions across use cases like fraud detection, customer service, risk analysis, and operations automation. 'Financial institutions are under pressure to operationalize AI faster, while managing risk, regulation, and complexity,' said John McCambridge, Global Head of Financial Services at Dataiku. 'This FSI Blueprint helps banks and insurers move beyond experimentation, delivering trusted AI agents that are observable, cost-controlled, and designed to deliver meaningful business value.' The Dataiku LLM Mesh offers native integration with NVIDIA NIM to simplify deployment of open, proprietary, and custom models within financial environments. Guardrails within Dataiku LLM Guard Services, such as Cost Guard and Quality Guard, provide built-in oversight, giving IT and product teams control over model usage, cost optimization, and performance evaluation. The collaboration between Dataiku and NVIDIA was unveiled during NVIDIA GTC Paris at VivaTech 2025. The FSI Blueprint represents the first in a series of joint initiatives to drive agentic AI innovation in highly regulated industries, with expansion planned into life sciences and energy. Financial institutions interested in deploying the FSI Blueprint can engage directly with joint go-to-market teams from Dataiku and NVIDIA.
Channel Post MEA
16-06-2025
- Business
- Channel Post MEA
Dataiku And NVIDIA Unveil FSI Blueprint AI Systems In Financial services.
Dataiku has announced a new FSI Blueprint for deploying agentic AI systems in financial services. This blueprint is designed to help banking and insurance institutions create, connect, and control intelligent AI agents at scale—with the governance, performance, and flexibility required for production in these highly regulated industries. This announcement builds on Dataiku's integration in the NVIDIA Enterprise AI Factory validated design, which helps enterprises accelerate the development and deployment of secure, scalable AI infrastructure. 'AI agents represent the next major shift in enterprise productivity, and banks are among the earliest adopters,' said Malcolm deMayo, Vice President of Global Financial Services at NVIDIA. 'This new bank blueprint from Dataiku, accelerated by NVIDIA, combines reusable components that enable banks to automate thousands of repetitive manual tasks. This allows institutions to deploy intelligent systems that can adapt to complex workflows and evolve responsibly over time—all while meeting regulatory and compliance requirements through central governance.' The FSI Blueprint combines The Universal AI Platform and Dataiku LLM Mesh with NVIDIA NIMmicroservices, NVIDIA NeMo, and GPU-accelerated infrastructure. It leverages AI agents powered by NVIDIA to provide financial institutions with a secure and modular foundation for building agentic AI solutions across use cases like fraud detection, customer service, risk analysis, and operations automation. 'Financial institutions are under pressure to operationalize AI faster, while managing risk, regulation, and complexity,' said John McCambridge, Global Head of Financial Services at Dataiku. 'This FSI Blueprint helps banks and insurers move beyond experimentation, delivering trusted AI agents that are observable, cost-controlled, and designed to deliver meaningful business value.' The Dataiku LLM Mesh offers native integration with NVIDIA NIM to simplify deployment of open, proprietary, and custom models within financial environments. Guardrails within Dataiku LLM Guard Services, such as Cost Guard and Quality Guard, provide built-in oversight, giving IT and product teams control over model usage, cost optimization, and performance evaluation. The collaboration between Dataiku and NVIDIA was unveiled during NVIDIA GTC Paris at VivaTech 2025. The FSI Blueprint represents the first in a series of joint initiatives to drive agentic AI innovation in highly regulated industries, with expansion planned into life sciences and energy. Financial institutions interested in deploying the FSI Blueprint can engage directly with joint go-to-market teams from Dataiku and NVIDIA. To learn from Dataiku and NVIDIA experts how to seamlessly integrate GenAI and agents across different compute environments and front-end applications, register for the FSI Blueprint webinar here:
