Within the last few years, the way we work has been completely overhauled by new workplace trends and technology. AI has rapidly redefined the rules of productivity in the business world; emails, social media posts, images, presentations, and videos can all be generated within a matter of clicks, not days.
But productivity is not defined by speed alone. Just as important are quality and outcomes. Yes, we are starting to entrust AI with increasingly important tasks, from driving to forecasting and even medical diagnoses, in some cases. However, there are still many things that benefit (and will continue to benefit) from having a person at the helm. Because the human touch has innate value. It promotes trust and connection in ways that machines are still far from replicating effectively.
What’s becoming apparent as AI adoption has accelerated is that its most obvious and easiest-to-attain value proposition is its ability to give time back to workers. It allows workers to focus on the most impactful elements of their roles, like bespoke problem-solving, acting as a partner to clients, and diving into buyers’ complex business requirements.
So in the era of generative AI, the question becomes: how can we use our innately human skills to not just drive productivity, but reshape how we think about it altogether? Below, we’ll explore the profound impact of AI on the workplace and the heightened importance of soft skills in the era of automation.
How AI has Shifted Workplace Dynamics
The workplace of today bears little resemblance to that of a decade ago, thanks to transformative shifts brought about by technology and evolving work culture. Generative AI tools like ChatGPT, Midjourney, and DALL·E are among the flashier uses of AI nowadays, but AI-powered analytics that analyze vast datasets, identify patterns, and generate insights have also brought immeasurable value to businesses.
Consider four types of AI-enabled data analytics:
- Descriptive analytics look at historical data to tell us what happened. This type quantifies, measures, and monitors objectively, like sales performance, sales-by-region, and win/loss reports.
- Diagnostic analytics tell us why it happened. Diagnostics use objective measures to help users better understand the subjective factors that led to the results. Diagnostic tools produce analyses for things like deal loss, sales cycle length, customer churn, and rep performance.
- Predictive analytics forecast what is likely to happen in the future using both subjective and objective inputs to score leads, anticipate churn, forecast demand and sales, and model the likelihood of specific deals closing. Critically, predictive models may use external signals and data―like overall market performance―to model trends in progress.
- Prescriptive analytics advise us on the next steps to take based on all of the above. Most people will be familiar with this branch of analytics from their personal lives. The same technology that drives Netflix, TikTok, and YouTube’s suggestion algorithms can weight buyer and seller actions to suggest what should come next.
Prescriptive analytics are where businesses can derive the most value and are the closest we’ve come thus far to replicating human ingenuity. These models turn insight into action and action into outcomes. These outcomes can then be codified for consistency and repeatability. However, they still require human oversight and collaboration.
As such, the integration of AI not only redefines the nature of work but will also continue to reshape the composition of the workforce. Organizations are likely to place a premium on individuals who possess a blend of technical expertise and soft skills, meaning it’s critical to not forget about the value of the human touch.
The Value of Soft Skills in an Automated World
While AI handles the routine and analytical aspects of a task, humans contribute their creativity, empathy, and critical thinking skills. Even the most advanced AI models today lack emotional intelligence, making humans integral in effective communication. Humans bring things to interactions that AI can’t; humans bring their life experience, the life experience of the person they’re listening to, and the ability to think through nuance that even AI can’t catch. And in the same way AI can train itself, humans are indispensable in coaching and mentorship to foster productivity in the workplace.
These soft skills are especially important in revenue-generating, relationship-centric activities like sales. For example, a sales manager is working with a new seller, and that seller is engaging with her direct point of contact (POC) at a prospect account. This earlier-career seller’s goal is to get the POC to introduce her to the VP of Sales because she knows the VP will ultimately be the decision-maker and needs to be involved in the evaluation process. But on a video call, the POC is reluctant to make the introduction. Perhaps the POC wants assurance that the seller won’t go “off script” and make him look foolish if he puts her in front of his VP of Sales.
Natural language processing (NLP) tools can be used to pick up on this hesitation, but interpreting the underlying reasons for it may not be within the solutions’ capabilities. That’s where the human element comes in, taking what the AI tool has provided and adding expertise and context based on experience. The manager, understanding the nuances of working with clients, can advise the new seller on how to handle the rest of the conversation to establish trust with the POC. As the conversation continues, this pivot guides the system’s follow-up materials to ensure an appropriate, tailored, and effective response.
This is just one of many examples of how humans inject value into activities that close deals and propel a business forward. In fostering interpersonal relationships, humans can also remember small details that show genuine care, find new ways to collaborate that fit employees’ specific needs or help to shape a supportive work environment. These things ultimately drive business outcomes, making them just as productive as AI’s automated task completion.
The Bottom Line
AI and advanced analytics have undeniably revolutionized the workplace, automating routine tasks and streamlining processes with unprecedented speed and efficiency. However, the essence of productivity transcends mere speed; it lies in the tangible outcomes that contribute to the success and growth of businesses. As AI handles the tedious and manual facets of tasks, humans emerge as indispensable contributors.
As we navigate the evolving landscape of work where AI and human collaboration becomes the norm, the symbiotic relationship between technology and human skills emerges as the driving force behind innovative solutions and lasting business success. In reshaping how we think about productivity, it is crucial to recognize and celebrate the enduring value of the human touch, which, in its multifaceted form, stands shoulder-to-shoulder with AI in producing meaningful business outcomes.
