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Are Agents the Future of Salesforce?

The news

Dreamforce 2024 has (almost) started and the announcements are pouring in. Unsurprisingly, many of them are about AI, generative AI, Slack, and of course, agents. One of the major announcements that Salesforce made these days is about the release of Agentforce. According to Salesforce, Agentforce is ”a groundbreaking suite of autonomous AI agents that augment employees and handle tasks in service, sales, marketing, and commerce, driving unprecedented efficiency and customer satisfaction. Agentforce enables companies to scale their workforces on demand with a few clicks. Agentforce’s limitless digital workforce of AI agents can analyze data, make decisions, and take action on tasks like answering customer service inquiries, qualifying sales leads, and optimizing marketing campaigns. With Agentforce, any organization can easily build, customize, and deploy their own agents for any use case across any industry. The future of AI is agents, and it’s here.

The platform is intended to bring chatbots to the next level by graduating them from co-pilots that “rely on human requests” to autonomously operating agents that retrieve the right data on demand, build action plans and execute these plans without intervention.

The bigger picture

According to Salesforce’s Trends in AI for CRM report, a staggering amount of 41 per cent of employee time is spent on low impact work. On top of this, 65 per cent of desk workers believe that generative AI will allow them to be more strategic. Salesforce also maintains that “every company has more jobs to be done than the resource available to do them.” Zendesk postulates that the number of interactions in customer service will grow by a factor of 5 in the near future and that of all resulting customer service interactions, 80 per cent will be resolved without human intervention. 

At the same time, many a business complains about a shortage in skilled work.

So, autonomous agents are clearly a kind of holy grail for software vendors, as they in theory allow their customers to scale with increasing demand in an efficient manner. Correspondingly, the heat is on, and agent has become the hottest buzzword in the current generative AI hype.

My analysis and point of view

I want to use this announcement to place some fundamental stakes in the ground. 

One is about the belief that autonomous agents are a silver bullet. Sorry to disappoint all drinkers of kool-aid: They are not.

The other one is about data. The perfect agent infrastructure will not deliver good results if the underlying data and the data used to train these systems, are flawed. For time being, this gets partly addressed by technologies like RAG and an increasing use of synthetic data, but this does not solve the issue of low-quality corporate data. This issue is also one of the root causes for the other one.

More on these points later.

Mark Benioff is bold as always by saying that Salesforce wants to “empower one billion agents with Agentforce by the end of 2025”. This is a little less than 1/8 of Earth’s current population. So, he either expects a lot of job attrition or he is talking about software agents. The latter might be a distinct possibility as, at least for the foreseeable future, software agents will be highly specialized. A deployment of meaningful size correspondingly requires a significant number of these agents. 

However, the more interesting question is how autonomous these agents can be. Their quality, and hence the customer satisfaction that Salesforce rightfully mentions as a core objective, heavily depends on data. And this data is regularly of poor quality. That is a problem. A big problem. This data problem is not new and needs to get addressed before a meaningful deployment of agents – or co-pilots, for that matter – can happen. Yes, agents can take over the more mundane tasks and are steadily moving into the not-so-mundane areas. The better this data problem is addressed, the better human as well as artificial agents can work. Again rightfully, Salesforce maintains that this is one of the core reasons to have Agentforce sit on top of its Data Cloud and are using Salesforces AI Trust architecture.

Still, this is one of the core reasons why agents in the near future will not be as autonomous as one wants them to be. I wished that Salesforce would have addressed this issue a bit more actively. Customers achieving a 40 per cent increase in case resolution which outperforms their old bot is great news, but it in reality tells only half of the story. 

Having said all this, I think that it is worthwhile for Salesforce customers to have a close look at Agentforce. However, I encourage them to do so with a clear plan of improving customer outcomes including customer experience, instead of looking at efficiency gains – aka laying off people. Not all of Salesforce’s customers will think like this. While there is no clear evidence that engaged employees lead to a higher customer satisfaction, it is quite obvious that empowering employees instead of antagonizing them and not creating anxiousness amongst staff reduces friction and therefore has a positive impact on productivity, if not necessarily customer experience. Still, improving customer outcomes is what improves business outcomes at the end of the day.

Salesforce could have strengthened this thinking by not choosing a consumption-based pricing but an outcome-based pricing, which is something that Zendesk recently introduced

All in all, with Agentforce, Salesforce delivered a powerful tool to its customers who with the help of Salesforce and system integrators can use it in very meaningful ways.

It will be interesting to learn more about how Agentforce will be deployed with which objectives and which KPIs business will use to identify a successful implementation. 

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