Rotate your phone

Once that's done you'll be able to
experience the OutsideThePC website perfectly.

Our Blog

How a VP of Engineering can Stop Fearing AI and Start Loving It
Back to Blog

How a VP of Engineering can Stop Fearing AI and Start Loving It

Despite the unprecedented growth and popularity of AI, many top executives continue to shy away from the technology – not realizing that AI is far from being a threat. In fact, it opens doors to several opportunities for businesses of all sizes. But fears around lost jobs, a shop floor full of machines, and loss of control often cause a VP of Engineering to stay away from the technology.

Read on to uncover the many myths surrounding AI and why (and how) a VP of Engineering can stop fearing AI and start loving it.

AI is not replacing humans; it is complementing them

One of the biggest apprehensions a VP of Engineering has with respect to adopting AI is the prospect of the technology wiping humans off the development landscape. Automated coding, testing, and deployment doesn’t exactly mean humans are redundant. The core purpose of AI is to support and aid humans in better doing their jobs; for instance, AI-enabled testing can automate the QA process, eliminating the need for humans to manually test each line of code. As a VP of Engineering, it is your responsibility to empower your team to act on the insights provided by AI algorithms and enable them to take necessary steps to further improve code quality and efficiency.

AI can result in unbiased outcomes if the proper data sets are chosen

Another common fear a VP of Engineering has is that AI algorithms end up providing biased outcomes – which isn’t always the case. Yes, AI can tend to produce skewed results, but that happens when the data sets that are fed into the algorithm aren’t all-encompassing. But since AI is only as good as the data it is trained on, if you are looking to use AI for requirements gathering, data analysts need to feed in data that takes a true and complete picture of the audience. That apart, it often comes down to the ability of the product development team to bake AI into the heart of the product. This has been a challenge on occasion since traditional product developers and testers are not always equipped to build or test AI products. This is why many VPs of Engineering turn to expert partners with the right combination of product development skills and AI knowledge to address these needs. You can combine the capabilities of AI with the expertise of such teams to improve the requirements gathering, definition, and management process and flag incomplete and ambiguous requirements in time, as well as build robust and resilient AI-powered products.

AI is not reducing control, but instead increasing it

As the volume, velocity, and variety of data continue to grow at an extraordinary rate, AI can lead to greater control. Using AI algorithms, a VP of Engineering can allow teams to more easily mine data for quality insight and clarity and make real-time decisions to satisfy customers as well as business objectives. By enabling humans to work faster and better than ever before, AI can empower even entry-level employees to automate menial tasks and make critical business decisions without having to depend on qualified data scientists. To ensure your teams are open to embracing the technology, it is important to provide them with all information they need about AI along with periodic training on how best they can make use of the technology to reduce their stress and improve their efficiency. The expert team we spoke of previously can also play a role by handholding your team through processes of transition.

AI can make good decisions with human oversight and governance

If as VP of Engineering, you fear that your AI algorithms may make bad decisions, you’re not alone. Despite all the capabilities of AI, the onus of evaluating the accuracy and efficacy of the results produced by AI lies entirely on humans. For instance, if you are using AI for rapid prototyping, to ensure the results of AI carry the required level of fairness and equity, you need human oversight and governance. Such oversight ensures AI algorithms don’t make the wrong choices, leading to more trust in AI and the results it produces.

With the right steps, AI can maintain privacy and security

When it comes to embracing AI in the engineering landscape, security and privacy are also of great concern. The belief that the parameters that enable AI algorithms to make predictions do not contain any traceable representation of the training data is not entirely true. With the right steps and techniques, data analysts can inspect AI models and make meaningful deductions about individual data points used for training the system. As VP of Engineering, you must make sure that your data sets are properly protected and encrypted, so you can reduce the likelihood of them falling in the wrong hands while also ensuring they are not susceptible to threats.

The opportunities and capabilities AI provides across every avenue of business is astounding. In the engineering field, AI offers several benefits across predictive analytics software design, requirements gathering, automated testing, error detection, low code development – the list is endless. Yes, like with any other technology, fears and concerns around AI are many. But with the right knowledge, approach, and tools, you can take the right steps in making the most of the popular technology across all of your engineering activities.