There's never been a better time for consultants! Examining IBM's new AI alliance with Salesforce

IBM has today announced a new collaboration with Salesforce, to help businesses accelerate their adoption of AI for CRM.

According to a statement from the two companies, the intention is to support clients in revolutionizing their “customer, partner, and employee experiences”, while also helping to safeguard their data. By putting IT and data leaders back in the driving seat of enterprise AI deployments, IBM and Salesforce say they hope to accelerate business transformation from the top down, rather than the bottom up. Inevitably, a big part of that focus will be on generative AI.

The collaboration is built on three key pillars, according to the companies. First, IBM Consulting will use its own delivery models, such as IBM Garage, to guide the enterprise adoption and integration of Salesforce AI technologies, including its own Einstein and that built into Sales Cloud, Service Cloud, Marketing Cloud and Slack.

Second, IBM Consulting will implement its own enterprise AI and data platform, Watsonx, as a complementary service.

And third, via IBM Consulting Managed Services for Salesforce, the two vendors’ shared clients will have access to a suite of AI experience and implementation accelerators to help scale and enhance Salesforce AI offerings.

I spoke to Matt Candy, Global Managing Partner, Generative AI, at IBM Consulting – a new role after 26 years at the company, most recently leading its customer transformation programs - about how the new collaboration fits with IBM’s strategic vision. He says: 

If I think about how we in IBM see the world, it's one that we believe is going to be very open. It's going to be very much focused on multi-model and multi-cloud approaches for clients. There's not going to be a ‘one size fits all’ solution to what they do around AI and generative AI within their organizations. So, we are super excited about what Salesforce has launched with AI Cloud, Einstein GPT, and all the capabilities within their platform.”

IBM has long been a key Salesforce partner, with 12,000-plus certifications in play, he point out, but that does not mean that the company is solely interested in implementing another vendor’s solutions:

Obviously, we'll be embedding deeply the certifications and skills around AI Cloud and Einstein GPT, leveraging that in the work that we do for clients. But we believe our unique differentiation is how we can bring our own tailored solutions and accelerators that wrap around the Salesforce platform.

For example, the work that we've done on our IBM Garage experience platform, which is our operating model for transformation. It's the approach that we use with clients for implementing and getting value out of the Salesforce platform. And we have infused generative AI capabilities into that, powered through our Watsonx platform.

Watsonx enables the delivery activities around Salesforce, when we think about things like user story generation, building out the value trees, and so on, and value realization. So, we've infused a bunch of generative AI capabilities into that.

He adds:

All the knowledge that we have within our organization from tens of thousands of implementations of Salesforce can help clients make better decisions. So, we are trying to help companies shift to delivery at the speed of AI. The speed at which this world is changing – every other day, there are new announcements and new capabilities – means that releasing the value of a platform like Salesforce is really important.”

Partners

There is a good cultural fit between the two enterprise giants, says Candy:

We see a lot of synergy between two companies. With AI Cloud and Einstein GPT, the ability to provide that kind of seamless AI support for employees. But in many of those interactions, there are data sources that sit in data silos around the enterprise. So, the ability to use Watsonx to extract insights from them and pass those seamlessly back into AI within Salesforce, and surface them back into CRM workflows, is another area where we see opportunity for ourselves in the consulting business. I don't think there's ever been a better time for consultants!

Bold words. So, in a world of burgeoning shadow IT deployments of AI – and comparatively little top-down, strategic adoption – is there also an opportunity to educate clients about the merits of managed, integrated enterprise deployment? He responds:

A solution to random acts of AI? Yes, I completely agree. Although this world has exploded this year, all the work that we've been doing for several years now in our data and AI business, and in Consulting, means we're 21,000-plus people helping clients adopt strategically and figure out how to unlock value within the enterprise. We have a lot of experience in helping them put the guardrails in place, and in the processes and procedures to allow this stuff to scale.

But often when taking a very systematic and strategic view, everybody always goes to employee productivity as a benefit. And certainly, that's one area. But we also see the ability to create new types of experiences, and new ways for brands to engage with customers.

We think about new business models. And the ability for organizations in different industries to consider new types of digital products and services, new platforms and business models powered with AI and generative AI, that can help them take a leadership position in disrupting an industry.  For example, building a large language model that's trained around the organization's brand, product policy, and campaign rules. The ability to use AI to drive quality, rigor, and control into that process. Thinking top down with a strategic approach is important.

How much is security a part of this collaboration? The bottom-up, shadow IT adoption of tools like ChatGPT risks divulging sensitive information to cloud-based AI tools. Can IBM help prevent that? Candy argues:

It’s an important part of it, yes. And I know it's an area that Salesforce takes very seriously too, with what it has been building around the Einstein Trust Layer, making sure that private data is retained within their environment. From an IBM perspective, our ability to bring our consulting experience in security and trust, together with what we're doing with Watsonx, is again differentiating for us, in several use cases for client organizations.

In some of those cases, they are going to need large language models that stay within their private cloud environments and are never going to be surfaced into the public cloud. And so, our ability to support them, through Watsonx, in the creation, training, and fine-tuning of those Large Language Models is a really important part of our strategy. Then being able to connect the data and the content back into Salesforce and surface it into the workflow of their platform, and into Einstein GPT.

He adds:

AI Cloud is certainly an area that we see is going to be very important in highly regulated industries that have sensitive datasets. So, for clients, understanding the models that they’re using, and how those models have been trained – and the datasets that they've been trained on, and the provenance of the data – is important.

Watsonx Governance is the platform that IBM has announced, a suite of governance tools that enable enterprises to manage that type of sensitivity. So again, we see a world with lots of collaboration opportunities together in this space.

Adoption

That aside, IBM and Salesforce were both early adopters of AI, and were early to market with enterprise AI solutions. So, have they been surprised by the sudden rise to power of OpenAI, with ChatGPT and the GPT engine becoming so critical so quickly to different industries – wisely or otherwise? Did anyone see that coming? Candy says:

I guess, [we're] surprised. But if I look at the technology that IBM has been building, and the work that we've been doing in Consulting over a number of years… [we were ahead of the game].  For example, I was with a banking client last week. We've been working with them for five, six years on their AI journey. A year ago, we were implementing large language models for them in customer service.

But what's great is that the world's attention has been captured. And, broadly, the world now has a better understanding of what these technologies can do, via what OpenAI have put in everybody's hands at a consumer level.

He concludes:

From an IBM perspective, our strategy is very much around AI for business. And how we can help enterprises shepherd in the use of these technologies. And there we see a world that is multi-model and multi-cloud. We are in a very hybrid world, and we see innovation moving faster in the open-source space.

IBM’s strategy has been very much around the ability to help enterprises bring in these capabilities, driving them in into the organization in a way that's safe for enterprise use. So, it's great that the world has woken up to the transformative potential.

My take

A promising collaboration that should help put the AI horse back before the AI cart, and so help IT, data, and business leaders realize the technology’s potential.