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Agentic AI is having a moment, as proponents see the benefits of using autonomous AI agents to automate manual tasks across organizations. Agentic AI, which Forrester named a top emerging technology for 2025 in June , takes generative AI a step further by emphasizing operational decision-making rather than content generation. The promise the approach has for impacting business workflows has organizations such as Aflac, Atlantic Health System, Legendary Entertainment, and NASA’s Jet Propulsion La
Once the province of the data warehouse team, data management has increasingly become a C-suite priority, with data quality seen as key for both customer experience and business performance. But along with siloed data and compliance concerns , poor data quality is holding back enterprise AI projects. And while most executives generally trust their data, they also say less than two thirds of it is usable.
Developers unimpressed by the early returns of generative AI for coding take note: Software development is headed toward a new era, when most code will be written by AI agents and reviewed by experienced developers, Gartner predicts. Organizations and vendors are already rolling out AI coding agents that enable developers to fully automate or offload many tasks, with more pilot programs and proofs-of-concept likely to be launched in 2025, says Philip Walsh, senior principal analyst in Gartner’s
Incorporating generative AI (gen AI) into your sales process can speed up your wins through improved efficiency, personalized customer interactions, and better informed decision- making. Gen AI is a game changer for busy salespeople and can reduce time-consuming tasks, such as customer research, note-taking, and writing emails, and provide insightful data analysis and recommendations.
Artificial Intelligence continues to dominate this week’s Gartner IT Symposium/Xpo, as well as the research firm’s annual predictions list. “It is clear that no matter where we go, we cannot avoid the impact of AI,” Daryl Plummer, distinguished vice president analyst, chief of research and Gartner Fellow told attendees. “AI is evolving as human use of AI evolves.
I have known for a while that setting the Data Category property on a column can influence the results you get from Power BI Copilot but I have struggled to find a scenario where it actually makes a noticeable difference. My sources on the Power BI Copilot team told me that Copilot does consider geographic categories (which are exposed in the Power BI Desktop UI) and date categories (which are available to set in tools like Tabular Editor but aren’t exposed in the Power BI Desktop UI; the
I have known for a while that setting the Data Category property on a column can influence the results you get from Power BI Copilot but I have struggled to find a scenario where it actually makes a noticeable difference. My sources on the Power BI Copilot team told me that Copilot does consider geographic categories (which are exposed in the Power BI Desktop UI) and date categories (which are available to set in tools like Tabular Editor but aren’t exposed in the Power BI Desktop UI; the
Today’s most effective go-to-market teams are increasingly embracing signal-based selling , a strategy that leverages real-time data and unique insights about promising prospects to gain a crucial edge in intensely competitive markets. Signal-based selling goes far beyond traditional lead generation or cold outreach leveraging basic intent data. Instead of waiting until buyers are clearly in-market, sales teams now can rely on a layered, AI-fueled analysis of multiple high-value signals to zero
Agentic AI, the more focused alternative to general-purpose generative AI, is gaining momentum in the enterprise, with Forrester having named it a top emerging technology for 2025 in June. Since then, several organizations have begun using the technology , and major vendors such as Salesforce and ServiceNow have offered AI agents to customers. Agentic AI focuses on performing specific tasks and emphasizes operational decision-making instead of the content generation often associated with gen AI
Business leaders may be confident that their organizations data is ready for AI, but IT workers tell a much different story, with most spending hours each day massaging the data into shape. Nearly nine in 10 business leaders say their organizations data ecosystems are ready to build and deploy AI at scale, according to a recent Capital One AI readiness survey.
While the ROI of any given AI project remains uncertain , one thing is becoming clear: CIOs will be spending a whole lot more on the technology in the years ahead. Research firm IDC projects worldwide spending on technology to support AI strategies will reach $337 billion in 2025 — and more than double to $749 billion by 2028. Those bullish numbers don’t surprise many CIOs, as IT leaders from nearly every vertical are rolling out generative AI proofs of concept, with some already in production.
Speaker: Jay Allardyce, Deepak Vittal, Terrence Sheflin, and Mahyar Ghasemali
As we look ahead to 2025, business intelligence and data analytics are set to play pivotal roles in shaping success. Organizations are already starting to face a host of transformative trends as the year comes to a close, including the integration of AI in data analytics, an increased emphasis on real-time data insights, and the growing importance of user experience in BI solutions.
CIOs are under increasing pressure to deliver meaningful returns from generative AI initiatives, yet spiraling costs and complex governance challenges are undermining their efforts, according to Gartner. Despite AI’s potential to transform businesses, many senior technology leaders find themselves wrestling with unpredictable expenses, uneven productivity gains, and growing risks as AI adoption scales, Gartner said.
Salima Bhimani has been encouraging the responsible and ethical use of AI for several years as Alphabet’s first chief strategist and director for inclusive and responsible technology, business, and leaders from 2017 to 2023. At Google’s parent company, she worked with moonshot companies such as Waymo, Wing, and X, to shape sustainable businesses and global impact.
From customer service chatbots to marketing teams analyzing call center data, the majority of enterprises—about 90% according to recent data —have begun exploring AI. However, there’s a significant difference between those experimenting with AI and those fully integrating it into their operations. For companies investing in data science, realizing the return on these investments requires embedding AI deeply into business processes.
CIO Jason Birnbaum has ambitious plans for generative AI at United Airlines. With the core architectural backbone of the airlines gen AI roadmap in place, including United Data Hub and an AI and ML platform dubbed Mars, Birnbaum has released a handful of models into production use for employees and customers alike. Chief among these is United ChatGPT for secure employee experimental use and an external-facing LLM that better informs customers about flight delays, known as Every Flight Has a Stor
In a world where uncertainty and change are constant, scenario planning empowers companies with the agility and competitive edge needed to thrive. Download the toolkit to fortify your business strategy , set up your competitive positioning , and ensure your company is poised to respond to any future scenario.
The world must reshape its technology infrastructure to ensure artificial intelligence makes good on its potential as a transformative moment in digital innovation. New technologies, such as generative AI, need huge amounts of processing power that will put electricity grids under tremendous stress and raise sustainability questions. But pioneering technologists are working on a potential game changer that goes some way to address these issues: photonics.
In 2018, I wrote an article asking, “Will your company be valued by its price-to-data ratio?” The premise was that enterprises needed to secure their critical data more stringently in the wake of data hacks and emerging AI processes. I wrote, “ It may be even more important for the security team to protect and maintain the integrity of proprietary data to generate true, long-term enterprise value.
Whether it’s a financial services firm looking to build a personalized virtual assistant or an insurance company in need of ML models capable of identifying potential fraud, artificial intelligence (AI) is primed to transform nearly every industry. In fact, a recent Cloudera survey found that 88% of IT leaders said their organization is currently using AI in some way.
Just as Japanese Kanban techniques revolutionized manufacturing several decades ago, similar “just-in-time” methods are paying dividends as companies get their feet wet with generative AI. “The timeliness is critical. You don’t want to do the work too much in advance because you want that real-time context. We activate the AI just in time,” says Sastry Durvasula, chief information and client services officer at financial services firm TIAA.
Whether your organization is at the start of its sustainability and impact journey or years into it, many brands share a common concern: the uncertainty of whether they are sending stakeholders mixed messages. Creating content that speaks to your audience's “love language” can be a tricky dance. But, worry not! 3BL has put together tips to ensure that your content not only finds its rhythm but also resonates with your target audiences.
When your CEO or CFO asks about the budget needed for technical debt remediation , do you find yourself struggling to justify the investment? You’re not alone. While CIOs understand the crushing weight of technical debt — now costing US companies $2.41 trillion annually — translating this into compelling business language for the board remains a persistent challenge.
As businesses increasingly rely on digital platforms to interact with customers, the need for advanced tools to understand and optimize these experiences has never been greater. Enter Gen AI, a transformative force reshaping digital experience analytics (DXA). Gen AI allows organizations to unlock deeper insights and act on them with unprecedented speed by automating the collection and analysis of user data.
Los CIO que sienten la presión de implementar proyectos de inteligencia artificial (IA) exitosos tienen una segunda preocupación: no tienen el presupuesto para llevarlo a cabo. El 90% de los CIO encuestados recientemente por Gartner afirman que la gestión de los costes de la IA limita su capacidad para obtener valor de esta tecnología. Además, si los CIO no comprenden plenamente el coste de escalar la IA generativa, podrían cometer errores de cálculo de entre el 500% y el 1.000% , según Hung
From obscurity to ubiquity, the rise of large language models (LLMs) is a testament to rapid technological advancement. Just a few short years ago, models like GPT-1 (2018) and GPT-2 (2019) barely registered a blip on anyone’s tech radar. But with the advent of GPT-3 in 2020, LLMs exploded onto the scene, captivating the world’s attention and forever altering the landscape of artificial intelligence (AI), and in the process, becoming an essential part of our everyday computing lives.
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An AI-powered transcription tool widely used in the medical field, has been found to hallucinate text, posing potential risks to patient safety, according to a recent academic study. And that tool is being used in a commercial medical transcription product that, worryingly, deletes the underlying audio from which transcriptions are generated, leaving medical staff no way to verify their accuracy, AP News reported on Saturday.
In today’s fast-evolving business landscape, environmental, social and governance (ESG) criteria have become fundamental to corporate responsibility and long-term success. Stakeholders—investors, regulators and consumers — now expect businesses to move beyond profitability and actively demonstrate ethical governance, social responsibility and environmental stewardship.
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Choosing the right business intelligence (BI) platform can feel like navigating a maze of features, promises, and technical jargon. With so many options available, how can you ensure you’re making the right decision for your organization’s unique needs? 🤔 This webinar brings together expert insights to break down the complexities of BI solution vetting.
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