The world of CRM has become a battleground for tech giants vying to harness the power of AI. Companies like Microsoft, Oracle, and of course Salesforce, are racing to integrate AI into their CRM platforms, promising businesses smarter, more efficient ways to manage customer relationships.
But with so many contenders in the arena, it can be hard to tell who’s winning, or even competing, in this CRM AI war. In this article, we’ll take a closer look at the strategies and innovations of the major players to determine who’s pushing ahead in this high-stakes race for CRM AI dominance.
Are “Bet-the-Company” Commitments to AI Risky?
This quick influx of AI use/integration that we’re seeing with Cloud vendors can be best described by the term “bet-the-company”. This signifies the high-stakes, all-in approach companies are taking to leverage AI technologies to transform their customer relationship management.
The majority of companies are investing millions, if not billions, into AI technology. However, the reason behind it has less to do with its capabilities and more to do with the pressure that is being put on companies to use it effectively.
In a recent study conducted by Slack, it was revealed that all executives feel pressure to integrate AI tools into their organization, with half of these executives saying they feel a high degree of urgency to incorporate AI tools. Simply put, Cloud vendors are going all in when it comes to AI in order to capitalize on the pressure that execs are feeling within their own companies to adopt these tools.
Using GenAI has its obvious upsides, with the main goal being to improve productivity and deliver an upgraded customer experience in terms of speed and efficiency – any Cloud vendor that is introducing AI into their space will tell you that exact statement. But what lies under that is the risk of putting your customer data at risk.
When it comes to sensitive data, companies are concerned that AI could access and use customer or business data in ways that weren’t intended. This could include sharing personal information, trade secrets, or financial data. As trust in data is the number one priority for all Cloud providers, this leaves many skeptical as to whether AI can be trusted or wired not to infiltrate this data. A Chevy dealership fell victim to this recently, highlighting the risks of exposing corporate data to chatbots and LLMs.
In essence, the bet-the-company strategy poses potent risks, but the pressure is on Cloud vendors to implement it safely in order to drive overall performance and stand out in the midst of the Cloud wars. With this in mind, let’s take a look at how Salesforce and its respective Cloud competitors are using AI.
Salesforce’s Einstein 1 and Model Builder
There’s no better way to start this discussion than with Salesforce, who has introduced some really exciting news so far this year in terms of AI. The introduction and rollout of Einstein Copilot and Einstein 1 is a game-changer for Salesforce users, enabling them to tap into the power of AI-driven automation.
“Our new Einstein Copilot brings together an amazing intuitive interface for interacting with AI, world-class AI models and above all, deep integration of the data and metadata needed to benefit from AI.” Marc Benioff, CEO of Salesforce
Copilot is like having your own AI assistant within Salesforce – it helps you get things done faster and smarter by learning from your past actions. It can suggest your next steps, automate tasks, and provide helpful insights when you need them. It’s like having a friendly co-worker who is always ready to lend a hand and share their knowledge to make your life easier.
Einstein 1 is the backend to Copilot, and includes the Prompt, Model, and Copilot Builder, enabling Salesforce professionals to build templated AI solutions to roll out to their users.
For example, sales teams using Salesforce can use Einstein 1 to help analyze customer data to identify patterns. Einstein 1 might notice that customers who bought product A often went on to buy product B within the next month. With this key insight, the sales team could reach out to customers who recently bought product A, offering them a special deal on product B. For more use case examples, read Christine’s ultimate guide to Einstein 1 here!
Salesforce has truly committed to the AI revolution, but there is still a long way to go for Einstein in terms of its effectiveness. Some would argue that its current functionality is basic and hasn’t shown many groundbreaking use cases as of yet. But, it is vital to mend the current trust gap between AI and its users – keeping things simple and laying the foundations before unleashing its full potential is more likely to do that.
How Are Salesforce’s Counterparts Using AI?
Salesforce is making its own strides, and that correlates with the current influx of AI use that we’re seeing across cloud companies. Let’s take a closer look at some of Salesforce’s competitors, specifically how they are using AI to improve their own platforms.
Snowflake
Snowflake are taking an aggressive approach to their rollout of AI by introducing technologies and solutions that will help their customers mobilize AI use.
The company have invested heavily in a relationship with Nvidia, a GPU company, to help them create a back-end infrastructure capable of delivering strong enterprise AI. Initially a significant factor in the gaming industry, Nvidia has branched into the lucrative world of AI. Its numerous capabilities, such as crunching massive amounts of data and powering AI algorithms, make it an invaluable asset for Cloud vendors. You’ll see them mentioned again later in this article.
Off the back of this, Snowflake has just announced their new LLM model, Arctic. It’s designed to be a cost-effective solution for enterprise A, and is optimized for SQL generation and complex enterprise workloads. Snowflake has claimed it outperforms other LLMs like Meta’s Llama 3 on certain tasks while using half of the budget that Meta used to build Llama 3.
“Snowflake Arctic is a leap forward in our mission to democratize data utility for enterprises. It’s designed to be robust and versatile, capable of handling the rigorous demands of enterprise data environments without sacrificing simplicity or efficiency for end-users.” Sridhar Ramaswamy, CEO of Snowflake
ServiceNow
Likewise to Snowflake, ServiceNow have also struck a lucrative relationship with Nvidia. The telecommunication company have two key goals in mind that they want to deliver with AI’s backing:
- Customer service: Use AI to guide agents, summarize calls and engage directly with customers.
- Incident management: streamline incident management workflows to AI. This could be creating tickets or summarizing situations.
The company recently announced a new update titled Washington D.C, highlighting their first steps into practical AI use. ServiceNow are keen on automating workflows using generative AI and providing simplified, easy-to-use ways to manage. Some of these new AI-powered features include:
- AIOps (IT Operations Management): This tool now uses generative AI to help IT teams solve problems faster by analyzing alerts and providing context to them.
- Virtual Agent: ServiceNow’s chatbot now has better AI, allowing it to understand users’ concerns more efficiently and provide more accurate and detailed answers.
IBM
IBM’s CEO, Arvind Krishna, has been vocal about his appreciation for AI and sees it as the future of IBM’s structure. However, this is likely to have a detrimental effect on many employees who work for the New York-based company.
Having taken a pertinent interest in AI for over 30 years, it’s no surprise that IBM are making the decision to rely on it wholeheartedly. In 1985, Deep Blue was unleashed, a IBM-powered supercomputer that was a chess-playing phenomenon. The computer took on world champion Garry Kasparov in a six-game match in 1996, where it lost four games to two.
IBM’s development of Deep Blue showed that AI could perform at a world-class level in a complex and strategic game like chess. This success inspired further advancements in AI technology, such as the development of IBM Watson, which used machine learning and natural language processing to win against Jeopardy champions in 2011.
IBM have further developed Watson and WatsonX, IBM’s new and improved AI assistant, and it offers a studio, data store, and governance toolkit for IBM users. It has already proved its capabilities to remove laborious tasks from workdays and automate IT issues, which likely explains the cuts for back-office roles.
Krishna has come out and said that he plans to suspend or slow hiring for about 26,000 non-customer-facing back-office roles, which amounts to roughly 10% of the company. IBM has already laid off employees in the communications and marketing division and there are clear signs that this could continue into other sectors of the company.
While cutting jobs for GenAI may give us harrowing insight into what lies ahead, IBM have benefitted massively from “betting-the-company” on it in terms of their stock value. The company’s shares have skyrocketed 19% since the start of the year and closed at $193.96M this month, just 6% off of its all-time high of $206.31M from 2013. Ultimately, the feeling at IBM is the latest layoffs and the upheaval of AI reliance is actually improving productivity and overall performance.
Workday
Workday have been building large language models (LLMs) for multiple years now, and are looking to further build on its capabilities. The company’s ultimate aim is to leverage generative AI for various language-related tasks, including natural language generation, document understanding, summarization, and augmentation.
They believe their approach to AI is different to their competitors, due to the unrivaled dataset they have in their arsenal that feeds their LLMs. They hold the largest set of financial and HR data, with over 625 billion transactions processed by the system every year.
Workday has taken a strong stance with their use of AI, understanding the safety precautions that come with it but fully committing to its full potential. Check out their in-depth artificial intelligence section on their website here – it finds the right balance between promoting AI for the future but reassuring users of the steps they are taking to harness it safely.
Microsoft vs. AWS
Microsoft and AWS (Amazon) act as the two biggest players in the CRM AI wars. Having both respectively invested the most money in AI development over the past decade, they are far and beyond the most successful cloud vendors revenue-wise.
However, AWS needs to invest more time in its AI developments if it wants to overtake Microsoft anytime soon.
AWS
Despite the success that AWS has enjoyed as a powerful cloud vendor in recent years, they have been left vulnerable by the current AI revolution.
Based on market share, AWS is still the “cloud king”. But AI is taking over, and their biggest competitors are leading the way. Analysts have described it as “Amazon being six months behind Microsoft with their AI development.”
A $4 billion investment in Anthropic, Open AI’s rival, puts them in a good position to start building effective AI tools, such as Rufus.
Rufus, Amazon’s AI shopping assistant, shows the company taking the right strides towards integrating AI tools into their daily operations. Rufus is trained on Amazon’s extensive product catalog and customer responses to help answer questions about products and help customers with different shopping needs. Early reviews say it performs well in its function (searching for products), but naturally needs work on handling nuanced queries and non-shopping questions.
Amazon’s CEO, Andy Jassy, is now taking steps to “bet-the-company” on AI, and believes that AWS’ developments will soon lead the generative AI charge:
“The amount of societal and business benefit from the solutions that will be possible will astound us all. We’re optimistic that much of this world-changing AI will be built on top of AWS.”
Despite the proclaimed six-month head start that Microsoft have, AWS’ ambition to develop AI, and develop it quickly, could change the landscape across 2024 and beyond.
Microsoft
Microsoft well and truly leads the charge of AI that we have seen across the last couple of years. The reason for this? A lucrative long-term deal with ChatGPT.
Microsoft’s early relationship with ChatGPT began with an initial investment in OpenAI, the company behind ChatGPT, in 2019. This partnership made Microsoft the exclusive provider of cloud computing services to OpenAI. Microsoft have continued to invest in OpenAI, with a multi-billion dollar investment announced in 2023.
Microsoft Copilot was released last year and uses all the power of the ChatGPT 4.0 model to help make suggestions for users on all their platforms. For example, Copilot might suggest a subject line or generate a thorough response based on what the email contains. In Excel, Copilot can analyze your data and suggest formulas or create charts for you. Hundreds of millions of people use Microsoft products daily – it’s a tool that will help just as many companies become more efficient and productive.
However, Microsoft’s new head of AI, Mustafa Suleyman, has raised personal concerns about the development of AI and has suggested that it might need to be slowed down before it gets out of hand. Ironically, this coincides with a recent statement from Elon Musk, who believes that a superhuman AI will be smarter than people next year (Although, he has been promising self-driving cars for a decade). Maybe Mustafa has a point…
Their success is clear, and it makes them the most successful Cloud Vendor in the AI wars. But with all the knowledge they are gathering and money they are putting into this process, are they on to something that may get out of hand?
Summary
Microsoft may be winning the battle at the time of writing, but the amount of investment we are seeing suggests that this war will only get more competitive. However, AI poses so many potential risks, and cloud AI vendors are embracing those risks to keep up in this race for AI supremacy.
What if AI begins to exploit customer information and ruin companies? What if Elon Musk’s superhuman AI prediction comes true? There’s still a lot of room left for mistakes and for this to get out of hand. However the possible upsides are too hard to ignore in terms of improving productivity and changing CRM platforms forever.
Do you think AI is getting out of hand? Make sure to leave your thoughts in the comments below!