Salesforce Launches AgentForce: A New AI Partner Network at Dreamforce 2024

Salesforce Agentforce AI and insights from Dreamforce - SiliconANGLE

Organizations in today's digital landscape rely on interconnected systems, meaning integrating platforms and unifying operations is critical. As AI becomes a bigger part of modern systems, technologies such as Salesforce Agentforce AI are drawn more in focus. Practitioners, meanwhile, have proven to be the biggest benefactors and influencers of data-driven markets. With its leading role in automation integrations, Salesforce Inc. has had its eye on the broader enterprise AI market. The company's plans around automation and for Salesforce Agentforce AI were a central focus of the recent Dreamforce event. "This Dreamforce could be Salesforce living the dream, bringing it all together and building those abstraction layers, and making gen AI to be the glue layer, so to speak," said John Furrier, executive analyst at theCUBE Research, during Dreamforce. "To bring it all together to abstract away all the complexity, reduce the steps it takes to get things done." The latest product announcements, new use cases and Salesforce Agentforce AI were explored by Furrier and theCUBE Principal Analyst Christophe Bertrand. They talked with industry executives and experts about the developments and innovations within the enterprise AI community. Here are three key insights you may have missed from Dreamforce: As mentioned, Salesforce has long held its reputation tied to its solid business. But with agentic systems hitting the scene, the company has a dream scenario on their hands, according to Furrier. "Salesforce, although it has disparate systems, has tons of data. They've got to use the data, they've got to get agents out there, they've got to protect the data," Furrier said. "It is a perfect scenario for them to be the poster child of how gen AI could transform an existing giant into a mega giant." As Salesforce integrates generative AI and data-driven strategies, securing and utilizing data becomes more essential. It's critical, and when a company spends a couple of billion on protecting it, it indicates how it is important, according to Bertrand. "It's about the essence of the business. It's about automating workflows. It's about leveraging all of that data that maybe you're actually not using today. Guess what? A lot of people here are probably underplaying their hands with their data right now," Bertrand said. "I think the promise of gen AI is, and AI in general within Salesforce ... is that it will bring a lot of automations and a lot of great things to the table." As the event played out, Salesforce laid out a path to infuse business processes with cutting-edge agentic AI. It indicated why Salesforce CEO Marc Benioff had suggested that the event would be the most important Dreamforce ever, according to Bertrand. "It's very hard to turn a platform company into an application company or vice versa. If they pull this off, they'll be one of the largest to have ever done it and they'll transform the company," he said during an event wrap-up analysis. "It's not just the Customer 360, but anything that customers choose to connect to the Customer 360 that can activate ... an agent. Salesforce becomes the platform on which others can build agents." At Dreamforce, discussions with executives touched on the role of Salesforce Agentforce AI, the company's major push to deploy AI agents on its CRM platform. Salesforce Agentforce AI represents the next evolution of the company's AI wave, according to Muralidhar Krishnaprasad (pictured), president and chief technology officer at Salesforce. "We had AI wave one, which was our Einstein predictive. The AI wave two is all our copilots with generative AI, and we're now entering the age of agents," Krishnaprasad said during Dreamforce. Agents are intended to plan better and do more complex tasks, and in many cases, it will eventually lead to the more autonomous AI, according to Krishnaprasad. At Dreamforce, the big announcement surrounded Salesforce Agentforce AI. "Our platform is going to be one of the most comprehensive platforms for agent development ... think about any business in the world. What do you do normally? You do advertising, marketing, you do sales, you do online commerce, you do service, you do analytics," Krishnaprasad said. "Imagine all of them on a platform on which you can now have agents that can help you through all of these process and more. That's our big announcement." Agentforce transforms customer interactions by integrating AI-driven agents with the company's trusted platform and Data Cloud, according to David Schmaier, president and chief product officer of Salesforce. All told, it's about Salesforce Data Cloud powering AI-driven customer experiences. "Our view is the data powers the AI and the agents, and the agents power the customer experience for the next generation. So, we've really brought it all together with Agentforce," Schmaier said. Here's theCUBE's complete video interview with Muralidhar Krishnaprasad: At Dreamforce, there was an emphasis on Salesforce's robust ecosystem, which will be key moving forward. That includes a strategic collaboration between Amazon Web Services Inc. and Salesforce Data Cloud. AWS and Salesforce have joined forces to streamline procurement for joint customers, with AWS Marketplace playing a key role. Many companies are saying they're using Marketplace with Salesforce to streamline procurement, optimize spend management costs and make things smoother when it comes to buying Salesforce products, according to Matt Yanchyshyn, vice president of AWS Marketplace and partner services at AWS. "Not only is it Salesforce with Hyperforce, we're excited how it's deployed on AWS, but even internally we use Salesforce, and that's at the root of the partnership," he said. "I use the Experience Cloud to build my Partner Central product. Our internal CRM is built on Sales Cloud. So we're big consumers and so we're partners in the true sense." The importance of strong partnerships was echoed during Dreamforce by Nick Otto, head of global strategic partnerships at IBM Corp. For IBM, if a company isn't driving different outcomes, at the end of the day, the value isn't going to land, according to Otto. "What we've done with watsonx Orchestrate in collaboration with Agentforce, we've been on this being able to get your insights and then drive different outcomes," he said. "That's all around automation and orchestration, which has been a focus of ours for quite some time." Dreamforce was also a chance to hear more about Salesforce's partnership with Canva Pty. Ltd., which involves AI-driven data autofill intended to streamline visual communication. Canva's Data autofill works in the Salesforce CRM, according to Rob Giglio, chief customer officer of Canva. "If you're a sales team, for instance, if I have 50 accounts, I don't want to go into 50 different presentations and add a logo, a name and business details," Giglio said. "Instead, what I can do is I can create an automated workflow using this brand new integration that just launched where I take Salesforce data, I autofill it into my presentations, and I can create 50, a hundred or 150 presentations in seconds." Here's theCUBE's complete video interview with Matt Yanchyshyn: Here's the complete video playlist, part of SiliconANGLE's and theCUBE Research's coverage of Dreamforce 2024:

Dreamforce 24 - Agentforce Partner Network - the SI perspective

There is concern in the vendor community that the AI bubble is on the point of popping before it is capable of realizing its potential. Following the release of OpenAI ChatGPT, organizations have taken LLMs and fine-tuned them. But to become an enterprise-grade software system an AI system needs a human/agent interface and a suite of tools to build and customize these systems. In short, there are an additional number of steps that need to be taken to get ROI from AI. And these steps include the need to integrate with a wide variety of partners to create an AI ecosystem around agents. This is what Salesforce announced at Dreamforce. Salesforce announced Agentforce at Dreamforce, a suite of autonomous AI agents that augment employees. Using Agentforce, organizations can add or configure jobs to be done for their agent in the form of topics and actions. Agent actions are automations. Topics define the guardrails, in natural language, and the set of actions that can be used within those guardrails. Agentforce comes with a library of standard actions, like "Summarize Record," "Plan my day," or "Process Return" with more being added. The Agentforce Partner Network expands on the Agentforce foundation with a library of pre-built partner agents, topics and actions to fast-track enterprises from DIY projects to professional grade solutions. Partner actions are already being built, for example Google actions that allow you to create, find, and share Google Docs and Slides, based on CRM data. Partner topics and actions can be used together to create partner agent templates. These templates assemble a set of actions and topics together into a pre-tested agent for specialized industry, line of business, or functional use cases. For example, organizations across highly regulated industries will be able to use pre-built agents from IBM to get work done without the cost or time of having to move data across systems. Customers will also be able to use pre-built agents from Workday, to streamline employee services like onboarding, health benefit changes, and career development, and from Certinia, to identify customer adoption risks and drive contextual engagement to proactively resolve issues and improve account health and value realization. The systems integrators' (SIs) role is to support enterprises in defining, building and deploying AI agents and actions using Salesforce Agentforce, leveraging their domain and platform expertise. To successfully and autonomously automate a task or sequence of tasks an AI agent needs to reason through a prompt, user intent or system event, retrieve data, build a multi-step plan, and take action to execute the plan. The more actions an agent can perform, the more capable at certain tasks it will be. However, Salesforce is well aware that the action may well require the agent to interface with another system or agent beyond the Salesforce platform. With the average enterprise managing nearly 1,000 different applications, AI agents will need the skills, data, and domain expertise to navigate across a network of multiple systems, databases, and other agents to get work done. Toby Astor, Salesforce COO Alliances and Channels, took the time to speak with me at Dreamforce about the SI role in the Agentforce Partner Network: We are bringing our partners in alongside our Salesforce technical experts to enable them on Agentforce and engage early in sales cycles. Further, we are connecting partners with our ProServe [professional services] organization to get quick, expert support as they engage with customers. We believe once customers see the value of Agentforce with a few use cases they will quickly want to expand their AI capabilities. To get customers started, we are co-investing with our global partners plus funding a number of services implementations to accelerate Agentforce. What is making Astor's job particularly interesting at the moment? Marc [Benioff, CEO of Salesforce] laid out a clear and compelling vision for AI powered agents that allows customers to simply get on with it and not rely on changing human behavior. Partners have a critical role to play in delivering this! Even though there are multiple powerful pre-built industry agent use cases, maturity of customer processes and their documentation is also an important dimension that has to be considered. For example, a small UK manufacturing company may be on top of their processes and so could stand up AgentForce incredibly quickly working with one of our global or regional SIs and drive significant productivity gains. There continues to be industry concerns about the level of AI skills and resources the SI sector actually has ready to help enterprises with their implementations. Astor thinks that one way for enterprises to gauge SI expertise is to think about the strengths of each player's data practices, because the ability to help enterprises work with their data is crucial in building agentic AI systems. This needs to be considered alongside known strengths in discovery processes and in process optimization. Astor continued: At Salesforce, we have created specific AI implementation ready criteria to guide our customers including Salesforce AI technical product certifications, AI thought leaders in their industries, and customer success. We showcase partners with AI implementation readiness in the Salesforce AppExchange. Ian Kahn is the founder and US leader of PwC's Salesforce Consulting Practice. His take on Agentforce is that:

Dreamforce 24 - Certinia steps up as one of the inaugural members of Salesforce's Agentforce Partner Network

Among the announcements at the Agentforce themed Dreamforce this year was the announcement of Salesforce's Agentforce Partner Network. This is a group of technology partners dedicated to extending the value of Agentforce for customers. Certinia is one of a few select partners working with Salesforce to build and distribute pre-built agents and agent templates. The plan is that these partner-built out-of-the-box agents will be deployed from the AppExchange, and can be set up in minutes with clicks, not code, and work just like the Salesforce provided out-of-the- box-agents. Certinia's planned Customer Success Agent, Certi, will be designed to identify customer adoption risks and drive contextual engagement to proactively resolve issues and improve account health and value realization. Certinia's core business is the professional services automation capability it provides via Certinia PS Cloud, which already has AI-enabled use cases available. For example, Copilot Actions for Services CPQ supports project scoping estimates, predicts payment delays, pinpoints resourcing bottlenecks and client dissatisfaction risks, as well as analysing historical data to optimise services and increase win rates while adhering to discount guidelines. Certinia has announced it will be developing several AI use cases to help transform Customer Success organizations using its CS Cloud by developing its Customer Success Agent. This is envisioned to transform customer success use cases like onboarding, success planning, and playbook automation, all while unifying customer data throughout the lifecycle. As a native Salesforce implementation, it will also draw on Salesforce Data Cloud and Slack integration and is being demonstrated to service customers now. Two of Certinia's CS Cloud customers, Dell and Salesforce spoke at a session held by the company during Dreamforce to discuss the evolution of customer success. Erica Lambert, Dell SVP, Global Channel, Alliances and OEM Services, is particularly interested in the road-mapped ability for AI agents to see CSM trends across the data and to enable the CSMs to pull this up to senior exec level reports. She is also looking to improve the quality of customer communication and to develop more orchestrators across vertical sectors. Jim Roth, EVP of Salesforce Customer Success said: Salesforce used to be shipping its organisation chart to customers and getting them to work out who to speak with, but now it is easier with CS Cloud to connect them to the specialists to answer customer queries. However, for the customer success team to work efficiently Roth said it was important to get the data house in order, pulling together transactions, marketing, events and purchasing history for example. Lambert agreed, adding that acquisitions made finding accurate account data more difficult. When it comes to CSM AI agents, Roth felt that the first benefit would come from the ease of summarising account information, and providing personas to give the most relevant information to each role. The AI agents will be able to understand the artefacts that make up an account and offer the summary data in the best way for different personas. Lambert agreed, adding that in an ideal world every customer would get their own CSM, and AI agents will help by being able to take calls and triage requests to increase effective communication. Salesforce implemented Certinia PS Cloud several years ago and when it came to choosing a CSM solution selected Certinia, because, Roth said" it is the only offering that is natively on the Salesforce platform, whereas the rest have connectors and Salesforce did not want to be using ETL tooling to get data to and from another technology stack. When it comes to transforming the CSM area, Lambert said: Sitting down with the customer to draw up a Customer Success plan is crucial. This is something Dell does with its top 2,000 customers. Today this is an intensive process and I expect it to become more automated going forward. You have to do this because if you do not have an agreed plan with the success path as a defined deliverable then you will struggle to meet expectations. You need an account summarisation that can be shown to customers. In this way you can use Customer Success as a differentiating factor. A topic that has been a discussion point at Dreamforce 24 is the growing number of consumption-based products such as Agentforce that Salesforce is now selling. From a CSM perspective Roth explained: Over the next year the CSM team will be tied to a Customer Success score since account expansion incentives for CSMs are a good idea if applied thoughtfully. Customer Success Manager teams are increasingly working in pooled shared service models to support many different customer accounts and are often also dealing with high staff attrition rates. In this context, AI-powered agents can help to proactively monitor customer health across the account, spot and prioritise potential risks, and suggest actions based on best practices, as well as provide consistency. For these reasons it is possible that Certinia's Customer Success Agent will contribute to the professionalisation of the Customer Success area by standardising best practice via the templates and enabling better measurement of how effective Customer Success is as a business area. In some organizations it may also help Customer Success Managers to develop Customer Success as a profit centre in its own right, rather than remain a business cost.