“Anything that’s invented between when you’re fifteen and thirty-five is new and exciting and revolutionary and you can probably get a career in it.”
It is precisely as a result of this theory by Douglas Adams, science fiction writer, that I decided to write about how AI, Artificial Intelligence to its friends, is literally changing the skills, technical competencies and mindsets of companies and professionals.
But that’s not all.
I think it’s interesting to spend some time reflecting on the new emerging professions that the overflowing “technology” river is bringing us at the moment.
Are you ready to find out a bit more?
Great, let’s get started!
The skills of the future: coding and philosophy
Mathematical, statistical and IT skills are, without a doubt, the first to be looked for by companies to implement Artificial Intelligence solutions within any business.
These are then followed by those concerning programming, in which the most used languages are certainly R and the commercial versions SAS, SPSS and Python.
Knowledge of all these tools, whose job it is to interact with data, is essential: SQL and NoSQL databases, or one of the many software dedicated to processing big data such as Spark or Hadoop.
Now, just imagine for a moment that your company has all the technical resources necessary to be able to make AI work to its advantage. However, how will it share and communicate the results emerging from its use with its stakeholders in a clear and accessible manner?
It is here that the cross-departmental team comes into play. Its humanistic and transversal skills, somewhere between technical and literary ones (experts in the user experience for example), act as a bridge between company needs and innovative projects.
Last but not least are those skills necessary to manage AI maintenance. In fact, according to a Google paper, this technology is “a loan with a high interest rate”. It requires much more maintenance compared with traditional software and, if not managed carefully, it could prove to be extremely risky.
It is, therefore, important to constantly monitor its activities and adjust the aim in the event of errors. Only in this way will it be possible to avoid pointless and harmful replications.
What are the new professions in the field of AI?
Now that we have looked at the necessary skills to take a project forwards where Artificial Intelligence is to be used, the time has come to speak about the professions that have developed alongside it.
To make things as clear as possible, I have decided to divide the new professional figures into two large categories: those who take care of Artificial Intelligence’s development and those who have a role in coordinating technology and corporate organization.
Three main professions can be identified:
- Data Scientist: this person takes care of advanced analyses and finding the most suitable algorithms to identify a phenomenon. This includes making the best decisions as a result to understand and manage it;
- Machine Learning Engineer: this profession perfectly complements that of the Data Scientist, developing AI algorithms and creating services that interface, also in real time, with other systems;
- Data Engineer: it is not possible to carry out analyses and develop algorithms without an adequate data collection infrastructure. This is precisely what the Data Engineer takes care of. They make the data available and usable for data scientists and machine learning engineers.
The need to coordinate the technical side of things with the corporate structure is a job for two important figures:
- Chief Artificial Intelligence Officer: even though their characteristics are not yet well-defined, their job is to create a connection between onboarding and operations. Indeed, it is important to create a focus and a corporate awareness surrounding AI to facilitate its introduction and use;
- Content Intelligence Manager: their aim is to guide the analysis and extraction of the data generated by the use of content with AI’s support. They are a cross-departmental figure that helps the different stakeholders to evolve their internal content management processes in order to ensure the benefits of Content Intelligence.
External vs Internal: Where to Find the Right Skills
One of the characteristics that makes the phenomenon of AI stand out the most is certainly its scarce nature.
Around the world, people with similar skills range between 200,000 and 300,000 in number, compared with a demand for millions. Not to mention those who take care of research aimed at improving existing algorithms. In this case, we are speaking about just a few thousand individuals.
For companies, there can be two main solutions in developing projects that envisage the use of Artificial Intelligence:
- Turning to external providers: results can be obtained “easily” and fairly quickly via specialized skills that do not, however, increase company know-how;
- Acquiring internal skills: the value generated would remain within the company. However, it could take much longer to track these skills on the market and give them the right importance within the organization. This is particularly the case if an AI project has never been managed before.
So, what should you do?
Well, when we talk about Artificial Intelligence, the only certain thing is change.
Only via continuous experimentation and the internalization of knowledge and skills will it be possible for companies to become the protagonists of the future.