Artificial Intelligence was first popularized by a small group of scientist gathered at the Dartmouth College in the United States in 1956. Since then, AI has advanced considerably and is powering many real-world applications ranging from facial recognition to language translators and virtual assistants such as Siri and Alexa. Still, we are far from witnessing AI-powered robots emulating humans. So far that is confined to the Sci-Fi movies. However, AI has created quite a stir in the business world with its many benefits and challenges.
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Below mentioned are some of the ways in which AI benefits businesses:
Enhances efficiency and profitability – AI automates routine based work thereby freeing up employees’ time to focus on knowledge based tasks. For instance, AI-powered systems can test humongous amounts of any data, and arrive at accurate outcomes in no time. With the help of AI-based tools, data analysis becomes faster and more accurate. This not only facilitates instant decision making but also enhances efficiency and profitability.
Enhances Employee Engagement – As businesses continue to look for new ways of growth, they need to manage their biggest asset – their human resource. The traditional engagement models that offer a one-size-fits-all approach to enhance employee motivation and productivity have become obsolete and there is a rising need for a personalized model to engage with every employee. A real-time data-driven approach towards employee engagement can not only boost employee morale but also adequately support business growth.
Enhances the pace of operations – If businesses want to stay afloat in these unprecedented times, then they have to move their operations faster. AI shortens the development cycle by cutting the time it takes to move from one process to another in the production environment. This saved production time results in faster delivery, thereby reducing the time-to-market.
Undoubtedly, AI offers a lot of benefits to businesses. However, at the same time its integration into already existing processes pose several challenges. Hence, enterprises need to plan the adoption of AI carefully and meticulously.
Below mentioned are some of the potential challenges worth considering:
A lack of Skillsets – The first barrier to successful implementation of AI is the lack of necessary skills. As per Gartner, most of the companies cannot do the AI implementation on their own because they do not have the desired skillsets. A majority of companies start their AI implementation journey thinking they can build the system by themselves, however somewhere along the way they turn to deploying AI by using embedded tools in intelligent enterprise applications. AI has been established as an industry trend. However, educational institutions still do not include this skill in their curriculum. This creates a huge skills gap in the industry. The only way to overcome this challenge is by upskilling and reskilling of the existing workforce. One way of doing this is by partnering with industry experts. Enterprises can partner with an AI expert to train and reskill their workforce.
Legacy Technology and IT Modernization – Often regarded as one of the biggest obstacles to AI adoption, a business without a modern technology infrastructure will always have difficulty in supporting AI implementation. Legacy infrastructure fails to support AI because of its inability to process huge amounts of data in real-time. AI needs an agile, flexible, and scalable IT landscape that is prepared to process data and run analysis in real-time. In such a scenario, cloud-native services have emerged as a viable solution.
Privacy and Data Security Issues – All AI-based solutions run on data. This data can be of confidential nature. Just like any other new-age technology, AI also brings a range of security and privacy vulnerabilities. Increasing dependence on AI for critical functions and decision making will not only create greater incentives for attackers to target those algorithms but also increase the severity of these attacks. To decrease the chances of exposure, strict control over the data on which AI-based solutions and systems are built is needed.
AI is here to stay and it will only advance further with time. Scientists and researchers are looking for more ways to integrate AI in our daily lives. This creates a need for building secure AI systems that can help businesses to enhance their knowledge and increase profitability and simultaneously reduce avenues for exploitation of this technology.