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Forbes
28-07-2025
- Business
- Forbes
Why Data Fitness Is The Foundation For AI Success
Maggie Laird is the President of Pentaho, Hitachi Vantara's data software business unit. We're entering a new era of enterprise automation, one where intelligent agents can analyze, decide and act independently. But while the industry's imagination races forward, infrastructure still lags behind. Ninety-three percent of enterprise IT leaders have implemented or plan to implement AI agents in the next two years, according to a recent survey by MuleSoft and Deloitte Digital cited by ZDNET. However, the survey also found that 95% of the IT leaders said they are struggling to integrate data across systems. Meanwhile, Gartner recently noted that, through 2025, 'poor data quality will persist as one of the most frequently mentioned challenges prohibiting advanced analytics (e.g., AI) deployment.' AI agents can only be as good as the data that feeds them. And most enterprise data environments are far from ready. They're fragmented. Opaque. Siloed by system, department, geography or format. Putting AI to work in those environments won't be transformative. That's automation built on sand. Enterprises are at a crossroads. Many are in the initial stages of deploying next-gen agents to boost productivity, streamline decision making and lower costs. But without a trusted, accessible and well-governed data foundation, those ambitions rest on shaky ground. AI agents don't just need data. They need data that is structured, contextualized, traceable and aligned to the organization's goals. Organizations must overcome a false sense of readiness. Think about what AI agents do: They generate signals, draw inferences and act. If they're trained on or use inconsistent or incomplete inputs, the decisions they make will reflect those flaws. While agents may move faster than humans, if they're working off half-truths or hidden assumptions, the consequences can quickly multiply. Thankfully, this isn't a technology gap. It's a data-readiness gap. And it needs executive-level attention. Over the past 20 years, my company has worked with some of the most data-intensive organizations in the world, from global banks and national defense systems to airlines, telecoms and critical infrastructure providers. Across these environments, four themes consistently separate those who scale well from those who stall and will be essential to an agentic world: 1. Build a unified, queryable data catalog. Most enterprises don't have a clear inventory of what data they have, where it lives or how it relates. A living, searchable catalog makes it possible for both humans and machines to understand and access what is available and use it responsibly. Organizations need to catalog both structured data and the rapidly growing pool of unstructured data, which makes up 80% to 90% of data today. Unstructured data is everything from videos to sales presentations to emails to social media posts that provide context for decisions. While this data will still likely live in different silos, a catalog is foundational to creating the data products that AI agents need to get a full picture of the business challenge they are addressing. 2. Operationalize data governance. Governance isn't about limiting access; it's about enabling trusted use. Yes, AI agents must know what data is relevant. But agents also must know how it was processed and what rules apply to its use. Think lineage, version control and explainability as baseline requirements. Every agent needs to know where the data came from, when it was changed, if it was changed, by whom and for what reason. For example, data may be scrubbed so voraciously that a person's middle initial gets removed in one dataset but not others. That can confuse an AI agent when, for example, gathering intelligence on whether a certain loan product would be good for a particular person. 3. Apply intelligent access controls. The data democratization that will drive agents doesn't mean letting every AI workload touch every dataset. It means giving the right agents access to the right data, under the right guardrails, for the right purposes. This requires policies that adapt to roles, risk levels and regulations. 4. Design pipelines for business relevance and scale. A smart pipeline isn't just fast; it's aligned. Different agents will need different datasets, formats, and levels of latency depending on the task. For instance, AI agents working on procurement will want and need access to different datasets than AI agents working on marketing. Once agents are working, monitor their success—or lack thereof—and make necessary changes in the data, the data pipelines and the access and control policies. Build data flows that can evolve with business needs and AI capabilities. Readiness is an ongoing practice, not a one-time project. Being 'ready for AI' isn't a one-time certification. It's a commitment to continuously refining how your organization collects, manages and mobilizes information. The companies that win with AI won't be the ones who adopt the most tools. They'll be the ones who do the most with what they already know and ensure their intelligence systems are built not just to automate, but to align. Make space for the agents of change, but first, build the conditions they need to succeed. AI is moving. Fast. The quality of your data will determine whether you're leading or watching from behind. Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?
Channel Post MEA
01-07-2025
- Business
- Channel Post MEA
NTT DATA Announces New Service for Salesforce's Agentforce
Following the unveiling of NTT DATA's Smart AI Agent Ecosystem , a transformative enterprise-grade framework for agentic solutions, NTT DATA has announced a new service offering for Salesforce's Agentforce that will help clients accelerate the adoption of autonomous AI agents to work alongside humans. The service will be delivered through an 'EPAS' model – Evangelize, Pilot, Adopt and Scale – and will work in harmony with NTT DATA's existing data and cloud offerings, including Agentic AI Services for Hyperscaler AI Technologies . Evangelize : NTT DATA will help evangelize the use of Agentforce, identify use cases and build return on investment proposals for adopting Agentforce. NTT DATA will leverage its domain-specific leadership, digital workforce expertise, and repository of hundreds of agentic AI use cases and roadmap, classified by industry, to align with what works best in each client ecosystem. : NTT DATA will help evangelize the use of Agentforce, identify use cases and build return on investment proposals for adopting Agentforce. NTT DATA will leverage its domain-specific leadership, digital workforce expertise, and repository of hundreds of agentic AI use cases and roadmap, classified by industry, to align with what works best in each client ecosystem. Pilot : NTT DATA will support a client's initial deployment and build the first use case as a proof-of-concept implementation of Agentforce. NTT DATA will advise on opportunities to add the power of complementary end-to-end AI agent ecosystem capabilities. : NTT DATA will support a client's initial deployment and build the first use case as a proof-of-concept implementation of Agentforce. NTT DATA will advise on opportunities to add the power of complementary end-to-end AI agent ecosystem capabilities. Adopt and Scale : Once the value of Agentforce is realized, NTT DATA will build a product-oriented delivery model to support scaling and adoption of Agentforce. NTT DATA will also reuse its extensive repository of Agentforce use cases to help its client get a head start on adoption. With the NTT DATA offering for Agentforce, clients can experience the benefits of robust solution architecture and services delivery capabilities, along with the opportunity to integrate with MuleSoft and Data Cloud. This multi-faceted advantage is rooted in NTT DATA's award-winning expertise in both integration and data unification platforms, providing clients with the comprehensive and tested scale required for global enterprises. Megan Piccininni, SVP and Global Salesforce Practice Leader, NTT DATA , commented, 'With our new service for Agentforce, our partnership with Salesforce underscores the transformative potential of agentic AI. Central to this innovation is the coordination and orchestration of multiple intelligent agents, which are essential for achieving comprehensive end-to-end automation across various platforms. Our Smart AI Agent Ecosystem, expert advisory services, depth of AI, data, and cloud talent, position NTT DATA as unique in this space with Salesforce. NTT DATA has been part of Salesforce's Agentforce Partner Network since its inception, and we are committed to deliver client success leveraging Agentforce.' Agentforce is a digital labor platform for enterprises to augment teams with trusted autonomous AI agents in the flow of work. With Salesforce's AgentExchange , a leading AI agent ecosystem for enterprises, clients have access to hundreds of ready-to-use actions, topics, and templates built by partners, and will have access to pre-validated Model Context Protocol (MCP) servers, that have passed rigorous security reviews to quickly create and deploy their digital workforce of AI agents. NTT DATA's new service for Agentforce is adaptable to different use cases. Clients will be able to benefit from agentic AI and see tangible outcomes across industries. The top use case for NTT DATA's service for Agentforce is focused on Customer Service and Experience. Application Management Services Agentification includes deployment of utility agents that interact seamlessly with various observability and service management ecosystems. includes deployment of utility agents that interact seamlessly with various observability and service management ecosystems. The service for Agentforce enables Agentic Business Process as a Service across different domains such as Life Insurance-as-a-Service and Contact Center-as-a-Service. across different domains such as Life Insurance-as-a-Service and Contact Center-as-a-Service. In Health and Life Sciences , AI agents can help transform patient management and improve patient outcomes. , AI agents can help transform patient management and improve patient outcomes. Real Estate and Vendor Management task automation, such as technical support, helps address changes and vendor management operations, reducing support tickets and manual process time. task automation, such as technical support, helps address changes and vendor management operations, reducing support tickets and manual process time. Seller Community applications streamline deal validation and sales intake, reducing deal approval time. applications streamline deal validation and sales intake, reducing deal approval time. Marketing Community use cases include automating email credit management and accelerating marketing email delivery, achieving faster email processing. use cases include automating email credit management and accelerating marketing email delivery, achieving faster email processing. Faster Time-to-Hire outcomes from optimized recruitment processes with Agentforce. outcomes from optimized recruitment processes with Agentforce. Governance and Security Control offer centralized management of security and reuse, ensuring consistency and control across all deployed agents. Digital labor is already here, delivering a meaningful competitive advantage for organizations that embed it effectively across departments. To truly scale this potential, businesses need clear insight into agent deployment, how agents enhance human productivity, and secure tool usage. Salesforce's latest Agentforce release provides an enterprise-grade platform to manage human-AI collaboration, connect agents to tools via open standards, and rapidly deploy industry-ready agents with the trust, scale, and performance enterprises demand. Agentforce expands digital labor across the enterprise with new industry-specific actions to provide industry readiness out of the box that delivers a fast path to value from AI agents. NTT DATA plays a crucial role in driving an agent economy with leadership scale and expertise and guiding clients in their agentic maturity , from task automations to interoperable agents, while helping to ensure responsible innovation and global governance. Megan Piccininni further added, 'In our role as an Outsourcing Service Provider (OSP), our competence to deploy the new service for Agentforce across industries differentiates us from the rest. By merging our competencies in Salesforce, Application Management Services, Business Process Services, Data and AI Services, Cloud and Security Services, and next-generation technologies, we deliver multi-faceted benefits to our clients. This integrated approach allows us to take ownership, manage, and operate within a business outcome-focused framework.' 'Organizations need a new labor model that unlocks the full potential of humans with AI at work. NTT DATA is a critical partner for identifying and developing specific use cases with our joint customers across industries, helping to ensure tailored and effective AI solutions for scaling digital labor,' said Phil Samenuk, SVP of Global Alliances & Channels and Outsourcing Service Providers, Salesforce. 'With Agentforce constantly evolving and expanding, NTT DATA's new service demonstrates the company's commitment to empowering customers to deliver success with Agentforce.'
Techday NZ
25-06-2025
- Business
- Techday NZ
NTT DATA launches EPAS service to boost Salesforce Agentforce AI
NTT DATA has introduced a new service for Salesforce's Agentforce, aimed at supporting client adoption of autonomous AI agents to work alongside human teams. The newly announced service follows the earlier launch of NTT DATA's Smart AI Agent Ecosystem, which provides a framework for deploying agentic solutions at enterprise scale. This service for Agentforce will be offered through an "EPAS" model—Evangelize, Pilot, Adopt, and Scale—designed to assist clients in every stage of agentic AI implementation and integration. Four-stage approach The "EPAS" approach begins with Evangelize, in which NTT DATA helps organisations identify relevant use cases for Agentforce and develops return on investment proposals tailored to individual client needs. The company relies on its industry-specific experience and a repository of use cases to align with the client's operational environment and strategic objectives. During the Pilot phase, NTT DATA supports the client's initial implementation of Agentforce, including building the first proof-of-concept use case. The company also advises on the potential benefits of incorporating additional AI agent ecosystem components. As clients transition to the Adopt and Scale phases, NTT DATA moves to a product-oriented delivery model to facilitate the widespread deployment of Agentforce solutions. The company's extensive library of use cases further streamlines this process, providing clients with pre-developed scenarios for rapid integration. Integration options The service enables integration with tools such as MuleSoft and Data Cloud, taking advantage of NTT DATA's expertise in integration and data unification. The company highlights the importance of offering a robust architecture and service delivery capabilities to support the requirements of global enterprises. "With our new service for Agentforce, our partnership with Salesforce underscores the transformative potential of agentic AI. Central to this innovation is the coordination and orchestration of multiple intelligent agents, which are essential for achieving comprehensive end-to-end automation across various platforms. Our Smart AI Agent Ecosystem, expert advisory services, depth of AI, data, and cloud talent, position NTT DATA as unique in this space with Salesforce. NTT DATA has been part of Salesforce's Agentforce Partner Network since its inception, and we are committed to deliver client success leveraging Agentforce," said Megan Piccininni, SVP and Global Salesforce Practice Leader at NTT DATA. Agentforce platform and use cases Salesforce's Agentforce is described as a digital labour platform that enables enterprises to augment their teams with autonomous AI agents directly integrated into their work processes. Through AgentExchange, organisations can access hundreds of pre-built actions, topics, and templates. The platform also offers pre-validated Model Context Protocol (MCP) servers that have met stringent security standards for rapid deployment of digital AI workforces. NTT DATA's Agentforce service is positioned as adaptable to various industry requirements and aims to provide business outcomes in sectors ranging from customer service to health and life sciences. Key use cases include Customer Service and Experience, management of observability and service operations, agentic business process outsourcing in domains such as Life Insurance and Contact Centres, patient management in healthcare, and task automation in real estate and vendor management. The company outlines additional applications, such as Seller Community platforms to reduce deal approval times, Marketing Community tools for automating marketing communications, and tools to speed up recruitment processes, among others. Centralised governance and security controls are highlighted as features to ensure consistency and management across AI agents deployed within an organisation. Scaling digital labour NTT DATA notes that digital labour is already providing a competitive advantage for organisations embedding the technology across their operations. Effective scaling, the company suggests, requires insight into agent deployment, productivity enhancements, and secure management of AI tools. According to Salesforce, Agentforce's latest release offers an enterprise platform for managing human-AI collaboration, connecting agents via open standards, and enabling rapid deployment of industry-ready agents with a focus on security and scalability. Salesforce has designed Agentforce to enable ready-to-use, industry-specific actions, aiming to provide measurable value for enterprise users. NTT DATA, with its industry reach and technical scale, plays a role in supporting clients' adoption of agentic models and guiding organisations in their evolution towards broader AI agent use while focusing on responsible innovation and governance. "In our role as an Outsourcing Service Provider (OSP), our competence to deploy the new service for Agentforce across industries differentiates us from the rest. By merging our competencies in Salesforce, Application Management Services, Business Process Services, Data and AI Services, Cloud and Security Services, and next-generation technologies, we deliver multi-faceted benefits to our clients. This integrated approach allows us to take ownership, manage, and operate within a business outcome-focused framework," added Megan Piccininni. "Organizations need a new labor model that unlocks the full potential of humans with AI at work. NTT DATA is a critical partner for identifying and developing specific use cases with our joint customers across industries, helping to ensure tailored and effective AI solutions for scaling digital labor. With Agentforce constantly evolving and expanding, NTT DATA's new service demonstrates the company's commitment to empowering customers to deliver success with Agentforce," said Phil Samenuk, SVP of Global Alliances & Channels and Outsourcing Service Providers, Salesforce.
Yahoo
29-05-2025
- Business
- Yahoo
Stifel Nicolaus Maintains Buy Rating on Salesforce (CRM)
On May 29, analyst J. Parker Lane of Stifel Nicolaus maintained a Buy rating on Salesforce, Inc. (NYSE:CRM) and kept a price target of $375.00. The rating update followed the company's fiscal Q1 2026 earnings report on May 28 and reflects the analyst's confidence in CRM's strategic positioning in the AI space and its considerable growth potential, driven by innovative solutions such as MuleSoft, Agentforce, Data Cloud, and Tableau. A customer service team in an office setting using the company's Customer 360 platform to communicate with customers. The analyst stated that management has also expressed confidence in the company's innovative technological capabilities, expecting them to bolster Salesforce, Inc.'s (NYSE:CRM) market presence and support revenue growth. The company's fiscal Q1 2026 results showed an 8% year-over-year growth in revenue which amounted to $9.8 billion. Its subscription and support revenue also increased by 8% year-over-year, reaching $9.3 billion. The analyst further commented that Salesforce, Inc.'s (NYSE:CRM) focus on adjusting compensation structures and expanding its go-to-market capabilities demonstrates a commitment to expediting growth while ensuring margin expansion. Although Salesforce, Inc.'s (NYSE:CRM) is in the early stages of monetizing its AI capabilities, the analyst expressed confidence in its potential to land multi-product deals. In addition, he stated that the company's traction in the mid-market segments and SMB points towards a promising outlook, supporting the Buy rating. While we acknowledge the potential of CRM as an investment, our conviction lies in the belief that some AI stocks hold greater promise for delivering higher returns and have limited downside risk. If you are looking for an AI stock that is more promising than CRM and that has 100x upside potential, check out our report about the . READ NEXT: and . Disclosure: None. Error 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
Yahoo
29-05-2025
- Business
- Yahoo
Informatica (INFA) Rating in Focus After $8 Billion Salesforce Deal
We recently published a list of . In this article, we are going to take a look at where Informatica Inc. (NYSE:INFA) stands against other AI stocks that are on analyst's radar today. On May 27, RBC Capital's analyst Matthew Hedberg maintained their 'Sector Perform' rating on Informatica Inc. (NYSE:INFA) and raised its price target to $22.00 from the previous target of $19.00. Informatica is a leader in enterprise AI-powered cloud data management. Analyst Matthew Hedberg cited Friday's Bloomberg report of takeover interest by Salesforce (CRM), noting that Informatica could be an attractive asset given key fundamental drivers. This includes the ongoing growth in data, the ongoing cloud mix-shift, and potential GenAI tailwinds. A business executive in a modern office looking over reports detailing artificial intelligence. The very same day, the news of Salesforce and Informatica agreeing for the former to acquire the latter for approximately $8 billion in equity value was confirmed on the respective companies' newsrooms. The acquisition is expected to boost Salesforce's artificial intelligence capabilities and give access to Informatica's data management tools. 'Together, Salesforce and Informatica will create the most complete, agent-ready data platform in the industry. By uniting the power of Data Cloud, MuleSoft, and Tableau with Informatica's industry-leading, advanced data management capabilities, we will enable autonomous agents to deliver smarter, safer, and more scalable outcomes for every company, and significantly strengthen our position in the $150 billion-plus enterprise data market.' Overall, INFA ranks 10th on our list of AI stocks that are on analyst's radar today. While we acknowledge the potential of INFA as an investment, our conviction lies in the belief that some AI stocks hold greater promise for delivering higher returns and have limited downside risk. If you are looking for an AI stock that is more promising than INFA and that has 100x upside potential, check out our report about this cheapest AI stock. READ NEXT: 20 Best AI Stocks To Buy Now and 30 Best Stocks to Buy Now According to Billionaires. Disclosure: None. This article is originally published at Insider Monkey. Error 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
