The present-day reality is that artificial intelligence is boosting Š ” Šand so is the market. AI and Big Data technologies can add significant value to a business, providing valuable insights about market trends and corporate processes, as well as predicting future sales, optimizing personnel and assets management and even taking on a part of research and development work.
Answering the demand, an increasing number of companies claim that they offer you the best AI solutions. How to choose a vendor that would have the necessary expertise, be reliable enough and suit your particular needs ̶ this are the questions that keep plaguing business owners and CTOs.
Knowing Tricks
First of all, let’s discuss how IT companies can persuade you that they offer AI solutions (when they don’t).
Calling something AI is not AI
Probably, the most frustrating trick: just rebrand software as AI without introducing any changes to it. A company may declare that they offer AI solutions, but it is absolutely critical to remember that not every software product that calculates something is AI. A statistical analysis is not AI. Nor is getting a result that you don’t understand.
Legacy software is not AI
So you have an old product which you wish to upgrade in line with the newest trends. Imagine you take an old car from your garage, install a propeller on its roof and start calling it a helicopter. Building AI functions on top of an obsolete code base gives birth to similar monsters unable to support AI at enterprise scale.
Databases are not AI
Many database vendors claim that it is AI they offer. Of course, AI is about big data, you do need a robust data analysis and databases do provide tools to handle data, so, they would say, a data platform is an AI platform. However, it is a fundamentally incorrect assumption, since AI and big data are inherently different. Big data is the raw input that needs to be cleaned, structured and integrated before it may be used, while artificial intelligence is the output, the findings that are drawn from the processed data. Which means that AI would require special tools and special skills on top of databases.
Company-Related Risks
Even if the company provides Artificial Intelligence services, it does not mean that it is reliable enough to trust it with a long-run project that needs continuous support and eventual modifications, updates and upgrading. A number of risks inherent to choosing a company on a booming market are related to the competition and a company’s life cycle, as well as their wish to provide the broadest range of services hoping to acquire the necessary expertise on the go.
Life and death of startups
AI market is relatively new and is populated with startups. Tech enthusiasts and entrepreneurs are attracted by the possibilities to find their own niche and test their skills. Still, 9 of 10 startups would fail and would cease their existence within three years. Besides, startups do not simply die: other companies acquire them, disrupting customers. The startup’s old clients may experience support issues and, in some cases, new companies would discontinue support altogether.
Subcontracting data scientists
Another problem with AI vendors is that they do not offer in-house solutions but rather hire data scientists who would do all the work behind the scenes. On the one hand, it offers value to businesses that need immediate results. On the other hand, adding a third party implies potential issues with the support of your product, knowledge transfer and team building.
Communication issues
AI is a complex technical field, with versatile techniques and subfields each having a language of its own. Machine learning experts think one way; experts in statistics another; they all have distinct terms and jargon. What is more, executives and business owners focus on business gains, whereas engineers are driven by technical challenges and innovative solutions. In other words, businesses need vendors or specialists who would bridge this communication gap. To control the situation, they need to look for AI vendors that can explain their work in plain language and deliver interpretable findings.
What Is a Trustworthy AI Vendor?
If you have decided to transform your business with AI technologies, you need to realize that it is a long process involving engineering, creating software solutions, staff training and changing business processes. To support you on this way, you will need a partner, not a subcontractor. Here are some aspects that you should consider while choosing who to trust:
Viability
How old is the startup you are going to work with? The first milestone is to survive one year within which most inefficient new businesses go down the drain. The second period to consider is three years after which companies become relatively mature and have a chance to be on the market for several years longer (the next threshold is usually around 10 years). That’s why check when the company was launched and carefully evaluate companies that are less than three years old: this would be a normal time frame for a startup to get a product into the market, acquire some customers, and get organized for growth.
Attitude
Startups are usually willing to please their clients but there is a big chance that they will be purchased by bigger players. Older and bigger companies offer greater stability at the expense of the vendor-customer relations. Furthermore, bigger vendors pursue profitability rather than growth. They may achieve it by cutting costs, with customer support being often the first thing to be cut off. Another way to improve profits is to outsource operations making the company you choose only a mediator between you and the unknown workforce.
AI platform
If you want to ensure that your AI project would serve you for a long time, check that the technologies behind it are modern and effective. An AI platform you are offered should be scalable, flexible and portable. At a certain point you may need to host your platform in cloud, on-premises, or a combination of both. A good platform allows changing your approach and is simple to deploy and manage without high maintenance costs. Another focus point is the software you choose. With the speed of change in technologies, open-source software becomes the only viable option that provides immediate solutions and adapts to the marker needs. In the AI era, it is open-source software that is the key to innovation.
Support of different users
Having AI does not equal to having a working API. Within a business, there might be diverse AI users who would require different applications, from an executive who would want dashboards to track overall results from the AI project to in-house data scientists who would want to code in Python or R and developers who want to integrate AI into their production applications. Besides, every user wants to work with AI with the tools they already use. Therefore, it is important to find a vendor that offers open APIs and business partnerships that make it possible.
Team
What do you need from an AI vendor? Is it just the application of the machine or deep learning algorithms to make use of already prepared data? Or do you want them to be in charge of the whole architecture of the AI project as well as of data collection and preprocessing? A vendor should be able to discuss all possibilities with you and offer you the team tailored to your needs, from domain specialists to AI architects, with the level of expertise varying depending on your goals. For a small-scale product, you should not be pushed to hire a room full of senior-level developers ̶ you might need only a couple of less experienced ones and an occasional supervisor.
A full cycle of AI development
It is crucial to look for an AI vendor that understands and supports the complete AI lifecycle and even more. Though every business wants immediate results, the introduction of AI into processes may require additional effort at any stage from data mining and processing, to machine learning, model deployment, monitoring and management and, finally, application development â‚‹ which is a multistage process in itself. Though it is the model we are hunting for, it is impossible to develop it without initial data preparation and it is useless without a corresponding application. Ideally, an AI vendor should be able to offer all stages of AI development.
Two-Way Process
We are, of course, fighting the urge to say that we are the best for the whole story and now it is our time! However, in reality, learning to be an AI vendor is a process in itself: to succeed we, as any other company, need to understand and adapt to clients’ needs. When we are talking about realizing that you do not need all-stars for every project, it is a result of our own experience: if you want to offer the best to a client, it takes a big step not to overload your seniors and admit that for most tasks you do not need the most experienced developers.
Now that we are approaching the 4th anniversary, we are heading towards the maturity and we know how to build a pipeline to cover all our clients’ needs at any stage of AI development or implementation.
