IDC have released new findings in collaboration with Salesforce. The study, which focuses heavily on the impact of generative AI on the global economy, also highlights the top challenges and benefits for organizations as they navigate this disruption.
Any seasoned Salesforce professional will be familiar with the IDC reports – and this edition captures some eye-catching figures all “fueled by [Salesforce] AI-powered cloud solutions”. The IDC estimates a potential net gain of $2 trillion for the Salesforce economy, as well as the creation of 12 million jobs globally between 2022 and 2028 – that’s in a matter of just six years!
What’s Grounding These Statistics?
First up, let’s briefly cover how far we’ve come. Looking back even 10 months ago, ChatGPT wasn’t the ‘household name’ it is today. We all heard about the record-breaking, rapid adoption of platform-agnostic ChatGPT – a million users only five days after launching – with the latest count at over 100 million users, with the ChatGPT website generating 1.6 billion visits in June 2023 (source: Exploding Trends).
It’s remarkable to see how ChatGPT and generative AI were being discovered and explored for the first few months following the tool’s November 2022 launch – compare that to the use cases we have for the technology now, and how generative AI has been ‘baked’ into platforms such as Salesforce.
Many tech executives, including those leading Salesforce, have used phrases such as “sea change” to describe the transformation we’re currently living through.
IDC described CRM applications as “beachhead solutions… identified for early AI implementation”. This is because the number of use cases is vast – primed for that all-important productivity boost.
Salesforce is a force to be reckoned with when it comes to the generative AI landscape, intentionally designing their offering with multiple competitive advantages, most notably:
- Einstein 1 Platform, with ‘Copilot’ set to work seamlessly alongside human users.
- Einstein 1 Studio, to empower admins to cater generative AI to their organization’s needs.
- Data Cloud, to power the rapid data connectivity required for surfacing insights from prompts.
- Einstein Trust Layer, to ensure that data privacy is adhered to when being processed by large language models on/off the Salesforce platform.
So, with this context in mind, we can start to see how these mega-figures have some real grounding.
The Salesforce Economy Impact
News came out towards the close of Dreamforce that Salesforce will be hiring 3,300 employees in a bounce back after their 10% workforce layoff at the start of this year. The main reason cited was Data Cloud – requiring both engineers to enhance the architecture, and salespeople to sell it. As we just mentioned, Data Cloud is the foundation that will power the rapid data connectivity required for surfacing insights from prompts – in other words, it’s the underpinning of generative AI capabilities on the Salesforce platform.
This is a bold decision from Salesforce, in terms of the number of hires, plus the fact that some will be ‘boomerang employees’ (laid off and rehired). Salesforce wouldn’t have taken this decision lightly without seeing true future demand here. Our prediction is that this will easily filter down to the network of Salesforce consulting partners, and Salesforce customer organizations could start looking for ways to implement and maximize generative AI.
The Salesforce Careers Impact
That’s a big increase, and hugely impactful for the global economy. Improving employee productivity (people doing their work more efficiently) will lead to business expansion into new areas that were previously impossible without automation.
However, it’s not all about the sheer generation of jobs; it’s also to do with the make-up of those roles. Future roles – plus re-skilling of existing roles – include data engineers, business analysts, AI solution architects, data architects, and data scientists.
Challenges and Benefits
With the rapid and prolific rise of GenAI, we’re no stranger to both the barriers and the benefits of embracing this innovative approach to our daily work lives.
Trust remains a key sticking point for some organizations, with 31% of those surveyed saying that a “lack of trustworthy data” is a top challenge to be addressed.
It’s clear that, for AI to be perceived as trustworthy and ethical, it must be fully embedded in applications and processes, with “policies and guardrails in place” – this will be a shared and evolving responsibility between employers and governing bodies.
A perceived lack of trust is compounded by the current lack of skilled employees required to implement and adopt AI processes and best practices – hence, the inevitable creation of so many AI-related jobs set to hit the market over the next five years.
On the flip side, it’s impossible to ignore the benefits of this inevitable shift to GenAI, from improved productivity and customer experience, to increased revenue.
Whether we’re ready for it or not, the work landscape will be transformed as a result of generative AI, so it’s best to prepare as early as possible.
While there will be some inevitable uncertainty, particularly around governance and regulations, there are countless potential benefits that are hard to ignore. Increased revenue will, of course, be a big driver for many companies, but employee productivity and customer experience are powerful motivators too.