The Power of Soft Skills. How Do We Keep Our Jobs in the Age of AI?
Why human work still matters
We are in the middle of a global technological revolution. Following in the footsteps of the Agricultural, Industrial, and Information Revolutions, this revolution is ushered in by what we call Artificial Intelligence or AI. It might not yet be obvious to everyone, but business is not as usual. The way we live and the way we work are about to change in fundamental ways. The very meaning and value of being human is about to be redefined. The magnitude of this change is not something we can pretend to understand. But what we can do is focus on what we at Cangrade understand best: what, in this brave new AI world, the relationship between people and work will look like.
Are we pondering here about a relatively distant future? Not really. Like every change, the transition to an AI-based economy will not happen overnight. but we are already in the early stages of this transition and the concept of acceleration is built into the very nature of AI. If you don’t want to be caught off guard, now is the right time to start thinking about this.
For millennia, people were hired for jobs because of their knowledge of how to do something and their mastery of tools. The contemporary reincarnation of this idea is known as “skills-based hiring.” Following this practice, companies are investing in identifying the critical skills required for success in their jobs and the tools to measure these skills in their candidates and employees.
While we live in the skills-based hiring era, something else is happening. Companies are increasingly treating skilled labor as a stop-gap solution. AI has already played a significant role in augmenting many jobs, making employees faster and more efficient. But there are reasons to believe that it will not take long before AI becomes a better option than a living and breathing employee for many jobs: a better coder, better forklift driver, better administrative assistant, etc. The list of potentially endangered skilled jobs keeps expanding.
Are we witnessing the end of Work? Are most of us soon to be replaced by all-powerful automation, with few remaining humans participating on the margins of productive processes and the rest subsisting without a purpose?
The absence of a place for people in this AI-powered economy is among the top concerns of AI skeptics and “doomers” (that is if we survive the robot apocalypses). This is not how we at Cangrade see it. People are hardwired to demand creative activity and contribution to something bigger than themselves. Moreover, they are the best consumers of everything produced, making them the engines of any economy. As such, they still have the power. We believe that the high demand for human purpose will create the market condition for people to stay relevant – and employed, if you choose.
With that in mind, people have a big advantage. This advantage is based on our bias toward other humans (yes, we still prefer humans to machines). It’s other humans who we develop a kinship with, relate to, and want to be around. As a result, we should expect more and more employment opportunities to be available in the space of human relationships. In the marketplace saturated with AI-produced goods, humans will give them a competitive advantage, and companies will need to adjust to this reality. New types of work and working collectives will arise for purposes other than brute force production, focusing on fulfilling human needs for purpose and connection (like art, care, entertainment, etc.)
Soft skills are the new hard skills
“Skill-based hiring” is inevitably about to transition into “soft skills-based hiring.” The main value of humans at work will increasingly be soft skills. Our work will depend not on our knowledge of tools, as AI will quickly out-compete us, but on our ability to be human. To understand, connect, and communicate with other humans. This is the new frontier, and this will drive the success of organizations in the post-AI revolution era.
What do we mean by this? Imagine finding yourself mistakenly overcharged by your financial brokerage. Suppose this is a very advanced firm using the latest AI technology to manage your account. Perhaps 5 minutes of interacting with it will resolve the problem. But here is what it will not do: it will not turn the bad experience into an opportunity to exercise empathy and care, rekindle the relationship, and ultimately win your loyalty and business for years to come. No matter how hard AI tries to emulate human touch, we will not see it as authentic and will not replace the real thing.
Unlike hard skills, soft skills are harder to identify and tie into job requirements. Moreover, soft skills are often viewed through pre-existing biases. For example, it’s common to refer to salespeople as “hunters” and to client managers as “farmers,” respectively ascribing to them stereotypical masculine aggressive or nurturing feminine traits. The data shows that these stereotypes are completely divorced from the personal characteristics that actually drive success in different sales teams. People are complex, and in contrast to hard skills, it’s a complex and diverse mixture of soft skills that drive success in sales, client management, or any other job.
It’s important to note that every job has a set of required soft skills unique to itself. While there is significant job-specific overlap, the soft skills unique to each team, company, market, etc., outweigh the commonalities they share with people in the same job title, market, or company.
Taking soft skills hiring into practice
Identifying and measuring this unique and complex mixture of soft skills for every job is challenging. Ironically, it’s AI that comes to the rescue. This time not to replace humans in their jobs, but to help them find the right job. The kind of job where their soft skills will allow them to be more successful and more satisfied with what they do.
Like always with AI, it needs a lot of data. But the good news is that even a medium-sized organization already has valuable data to learn from their existing employees, and it will be a great starting point for building a soft-skills-based job success model to identify just the right combination of soft skills for success in their roles.
What kind of data are we talking about? As an example, Cangrade’s AI is trained on these types of input:
- Employee personal qualities
- Employee job metrics
- Employee retention, satisfaction, and job engagement
- Qualitative feedback about what is seen as important for success in each job
These inputs create tens of thousands of data points for AI to learn from, for even relatively modestly sized teams and organizations. The resulting AI-built success models reach a predictive validity that far exceeds that generated by evaluating candidates on their hard skills, even when they are relevant. The R2 for soft skills-based AI is 50-60%, whereas the R2 for hard skills testing is = ~20%.
These complex soft skills-based models also have a much lower risk of biases than traditional hiring. Cangrade takes it further and uses its patented technology to remove any biases from the resulting models, even when they creep in.
Another beautiful aspect of soft skills-based hiring is that soft skills are universal. The same soft skills can make you a superstar in one job and a failure in another. This allows an employer to evaluate a candidate for any number of jobs at the same time, and a candidate to apply for any number of jobs at the same time (another area where Cangrade holds a patent). Just think about the implication of this for how the entire job market functions.
No right soft skills? No problem
Now that we have, hopefully, convinced you about the benefits and the importance of soft skill-based hiring in the age of AI, and given you some idea about how it works, let’s talk about professional development. What will professional development look like when you and your employees’ main skills are mainly soft skills?
For decades, every role has been associated with a set of skills, hard or soft. This skill set guided the professional development of employees based on their career path. This type of professional development has been losing relevance, primarily due to the dynamic nature of skills and competencies in today’s jobs and a total lack of personalization. AI will inevitably deal another blow to this old approach by making hard skills increasingly less important and soft skills increasingly more dynamic and personalized.
Just like neither nature nor nurture alone makes a person who they are, employers can not rely solely on recruiting or solely on professional development to have the best employees. A truly strategic organization will always want these two components to work in concert and be guided by compatible objectives.
In the universe where soft skills are prevalent, we can redeploy our AI soft skill-based success models to focus on development priorities. These priorities can be highly personalized for each employee in the context of their current or prospective job. This personalization will improve the metrics that are important to each organization, be it performance, job satisfaction, retention, or anything else.
This type of professional development is already a huge leap forward compared to the old static, role-based, cookie-cutter development plans. But we are only scratching the surface of the possibilities for professional development in the age of AI. What comes next is a complete personalization of the learning content driven by these priorities. Personalization parameters could include the role, industry, and market, as well as individual characteristics such as motivations, attention patterns, information consumption preferences, etc. This way learning will be extremely relevant, highly engaging, and delivered in the way each employee prefers.
If this sounds like an excessive expression of AI optimism, that’s because it is. AI is capable of many things. It’s capable of displacing people from jobs, but it’s also capable of making people more professionally fulfilled and satisfied with their jobs and lives. The direction it goes is still up to us. It is also up to us to demand much-needed AI safety guards, guidelines, and regulations from our governments.
We are at a critical juncture. We hope that what we outlined here gives you a better idea of how AI can help people continue to be a productive force and be better humans. Let’s work together to shape this type of AI future for ourselves and the next generation.