Over the past decade, artificial intelligence (AI) has transformed from a futuristic concept into a raft of real-world technologies. Today, businesses can no longer sit idly by while competitors exploit AI to pad their bottom lines. However, launching a haphazard AI initiative could be costly and ruinous for any company. To avoid that, it's vital to approach the task deliberatively. Here's a step-by-step guide on what to do.
Select Appropriate AI Technologies
One of the challenges businesses face when looking to exploit AI is that it's a broad discipline. Therefore, developing a business case that identifies which types of AI the company wishes to use is necessary. That starts with understanding some of the broad categories of AI solutions available to businesses. For companies seeking expert assistance, exploring AI developers for hire with Mobilunity can be a strategic way to access top talent and implement AI solutions effectively. Let's explore the following categories.
Robotic Process Automation
Robotic process automation (RPA) is a discipline devoted to smart automation solutions for business workflows. Basic RPA solutions excel at automating repetitive tasks. However, AI-infused RPA solutions can handle far more than that. They can, for instance, overcome issues stemming from unstructured data inputs to create reliable automations. For example, AI RPA solutions can enable incoming business invoice analysis without standardization. That can streamline the process of getting the correct invoices into the right employee's hands with fewer errors. Moreover, AI RPA solutions can learn as they go, so they won't require reprogramming as the data inputs change.
Generative AI
Of all the AI categories, none receives more buzz and attention than generative AI. It's the category that covers machine-learning systems that simulate human-like creativity. It includes things like AI chatbots as well as image and video generators. Businesses already have countless uses for the technology. For example, it can assist with rapid prototyping or the creation of marketing media. Generative AI is also undergoing some of the most rapid development of any other AI discipline. So, it's likely to become even more useful in the future.
Data Analysis
Another type of AI technology making its way into business operations is solutions enabling high-volume data analysis. AI excels at pattern recognition and anomaly detection, making it a natural fit for analytics. Some of the popular applications include automated data cleaning and processing, as well as information extraction. AI solutions in that area can reduce the workload on human analysts, freeing them up for interpretation tasks rather than preparatory ones.
Identify Necessary Job Roles
For a business, deciding on areas of focus for an AI initiative allows for identifying needed job roles to support it. That's the first step in figuring out how to get the right talent onboard to make the initiative a success. Commonly needed specialists include:
For businesses with no prior AI experience, hiring a data scientist is often the best first step when building an AI team. They'll have a broad understanding of how the business's available data can drive AI-powered solutions. They can also help validate the business's idea of applying AI to their chosen business processes. Best of all, they'll know what specialists to hire to build or integrate the necessary AI solutions.
Choose Between In-House and Outsourced Staff
Hiring the necessary staff for an AI project can be difficult and costly for the average business. That's because the industry has a talent shortage, and the firms with the deepest pockets usually win any hiring competition. For SMBs, it could take years to build a complete in-house AI team, if they can do it at all. However, having an entire team in place at the outset of an AI initiative is usually unnecessary. Plus, there are other ways to plug talent gaps.
Outsourcing is often a preferred solution for businesses to overcome AI hiring challenges. That's especially true for some of the discipline's more technical roles. It can take months to hire AI developer candidates suited for a specific AI initiative. However, an outsourcing agency can supply the necessary talent almost immediately. Plus, the cost of outsourcing specific roles is often far less than hiring to fill them. For example, the average AI engineer in the US makes approximately $210,595 annually. An overseas AI engineer may make a fraction of that. So, even with an outsourcing agency's profit margin built in, most businesses save money using outsourced talent.
Define Initiative Steps and Delegate
With staffing settled, the final step in launching an AI initiative is to lay out a development plan and delegate tasks to the relevant workers. For businesses developing AI tools and solutions from the ground up, this job is best left to a chief data scientist and an AI product manager. Between them, they'll decide on the features required of a minimum viable product. Then, they'll create a roadmap and get the team working.
An AI engineer is typically the appropriate project leader for businesses whose AI initiatives involve using existing AI solutions. They'll understand how such solutions can best integrate into existing business systems. For any necessary customizations, they may work hand in hand with a software developer and a data scientist.
Test, Iterate, and Succeed
Launching an AI initiative is one thing, but ensuring it succeeds is another. One key to doing that is understanding that most AI projects fail—at least initially. Long-term success typically requires significant patience and a willingness to test and iterate solutions to work out problems. That process can take quite a while and requires consistent investment. However, businesses that stick with their plans and see them through will reap the rewards that AI has to offer. And that is the true measure of any business AI initiative's ultimate success.