Editor’s Note: This is a guest post by Lilou Hoffman with The Negotiation Experts. Her opinions are her own.
The fourth industrial revolution is centered around the tech industry. Artificial intelligence (AI) and machine learning (ML) are skills that are highly in demand.
However, there is a shortage of these highly sought-after skills. Because these skills are so new, many potential trailblazers of tomorrow are still in college studying to become AI and ML engineers. Those who are qualified for the job may have their options wide open when negotiating employment contracts.
Businesses are looking for employees with solid reputations and exceptional skills. At the same time, they need to source the best-qualified and most-experienced employees so that they remain at the forefront of technological advances.
Employees have a profound effect on the future of any organization. That’s why an employer has to pay handsome salaries and make their employment offers attractive in order to secure the best people in their field.
If your organization needs to recruit and retain skilled professionals, you will need employee procurement negotiation training. A recruitment executive, who recently graduated from our contract negotiation training in LA, shared with us how he is now enjoying greater success in winning over talent from his bigger competitors. The key for this executive has been negotiating customised, mutually beneficial employment contracts.
It’s not easy standing toe to toe with tech giants such as Facebook, Google, Microsoft, and Amazon. Big companies offer talented employees premium salaries and benefits, as well as bonuses. Meanwhile, many AI and ML engineers are starting their own business to make their own millions, narrowing the pool of potential employees even further.
How can your organization possibly compete with all these external factors and still find the right person for the job? So, instead of hiring a full-time AI and ML engineer, you may choose to engage the services of a consultant.
However, consultants can be fickle, so your negotiation skills need to be on point. You need to assess the needs of your company so that you target engineers with the skills you require.
There are many fields of specialization within the AI and ML sector. That’s why you must understand what services you need, though it can be a bit daunting to understand all these fields.
Here’s a basic breakdown that you might find helpful:
1. ML is a field where the engineer creates and installs self-learning software. ML makes a machine or app acquire more knowledge and become smarter as it is fed more data. Advanced technologies work according to the idea that a computer system can learn from the data it gets, determine patterns, and then make decisions without relying on a human being.
2. Neural networks are computer systems that are inspired by a human brain. Networks play a great role by facilitating a computer’s ability to learn more and improve on an ongoing basis. The engineer trains the computer. As a result, the computer generates an independent way of analyzing the data. An example is when your Gmail account generates a smart reply for you to use when replying to emails.
3. Deep learning is linked to neural networking on several levels and is also modelled on the human brain. An example of this is a filter for your news stream that excludes negative news and only focuses on the good news.
4. Data science does not always require an AI engineer. Data science is the process of data analysis. Such a process does not require algorithmic programming and does not include computer learning mechanisms.
5. Natural language processing allows computers and human beings to speak the same language. These processes are time consuming, as you need to slowly teach the computer to work with the intricacies of the human language. This programming can be utilized in the customer service industry, where customers can ask a question, and a computer can understand and respond.
6. Big data is a form of programming that allows the analysis of huge amounts of data daily.
All the fields described above fall under the umbrella term of AI. AI is defined as programming of a computer using algorithms. A computer must learn from the receiving data and respond more effectively. AI is a field in which computers are taught skills and intelligence that, previously, only humans possessed.
Now that you’ve determined what services you need, you can set about the recruitment and contract negotiation process.
Technical skills are important. If you’re dealing with an engineer with experience, check for a proven track record . Or else, don’t assume that experience is everything. You can give a less-experienced engineer a coding test to see if they’ve got what you’re looking for.
Communication skills are necessary for a successful AI engineer. The engineers spend their time programming and ‘talking’ to computers. However, you must ensure that the employee can communicate verbally and write to his team and organizational management.
The capacity to adapt to an ever-changing industry is necessary. This industry is advancing and changing at such a rat, that an engineer needs to keep up with developments and be able to apply them. An AI engineer needs to be creative and willing to come up with less obvious solutions to problems.
Being goal-oriented and responsive to deadlines is important as well. The AI engineer must be able to work according to deliverables and timelines.
Look out for freelancers on the different platforms the internet offers. Alternatively, you can turn to an agency for help.
In an interview, ask questions related specifically to what your organization needs. Give the applicant a practical assessment if necessary.
Once you’ve narrowed down the field, put your employment contract negotiation skills into practice. In most cases, top AI engineers have the advantage. You need them more than they need you because the demand for their skills is so very high.
If you enter contract negotiations with a flexible attitude, you’re likely to get a similar response from your applicant. Be prepared to shell out more money than you’d like, but balance that against the skills brought to the table.
Think about the impact this appointment is going to have on the future of your organization. Most companies are now budgeting huge sum of money for the employment of tech specialists than ever before.
Some AI engineers may prefer to do a lot of their work offsite. Engineers might not be willing to commit to one organization and may work on a consulting basis, since the challenges offered by different organizations stimulate their creativity. An AI engineer may have their own flair and style, and your contract negotiations need to take this into account.
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