The dependency on automation has accelerated due to COVID-19 pandemic. Therefore companies are relying on emerging technologies like artificial intelligence (AI) and machine learning (ML) to have business continuity amid this crisis. AI and ML are not only transforming the way businesses operate, but also providing a massive opportunity for companies to gain a competitive advantage.
However, due to several reasons – like lack of skilled talent and budget, along with an understanding of newer technologies – have created a host of barriers for enterprises to smoothly adopt artificial intelligence and machine learning for their organisations. In fact, according to a recent survey, approximately 50% of respondents reported that their organisations lack skilled talents to implement real AI. The study further stated that another 21% of respondents believe that their organisations have no aligned technology infrastructure to support advanced AI.
Some of the other challenges mentioned were lack of tools, no access to required data etc. Companies also go through an inner dilemma of introducing artificial intelligence in their organisation, which in turn, acts as a barrier for businesses to leverage the full potential of emerging technologies. In this article, we are going to share a few ways companies can smoothly adopt artificial intelligence and machine learning in their organisation to enhance their business productivity amid this crisis.
Creating a strategic approach
To get the most out of artificial intelligence, businesses must understand the potential benefits of artificial intelligence and how it can be used to transform their businesses. Such an approach needs strategic planning, where businesses need to define their objectives and plans that can help the company grow and develop. Although businesses understand the advantages of artificial intelligence, they fail to create a clear strategy to roll out AI-based projects. Enterprises, sometimes, also struggle to identify areas of their business where artificial intelligence can be applied to gain benefits.
According to a recent report, only 17% of respondents stated that their companies have mapped out potential benefits of artificial intelligence in their organisation, where only 18% of respondents indicated that their organisations have a clear strategy in place. Many businesses use artificial intelligence to enhance their customer experience by implementing predictive analytics on business operations. Others use AL and ML to gain real-time monitoring of their supply chain, which in turn, can improve the business bottom line.
A lot of this could also be attributed to organisations’ lack of data literacy, which is extremely critical for businesses to understand deployment of newer technologies. Many companies still work on silos and therefore lack data readiness, which act as a massive barrier in adopting artificial intelligence. To make your organisation data-ready, business leaders need to empower their employees with data access as well as train employees with data literacy programs. Business leaders also need to have a comprehensive approach to the company’s data strategy where they need to understand the importance of data for business relevance as well as its availability, security, and governance.
Fill the existing skills gap
With these novel technologies penetrating the industry, it has created a huge skills gap, which has surpassed the demand for skilled AI talents. Therefore, organisations are struggling to hire talented professionals to lead their AI-based projects, which in turn, slower their process of achieving their business objectives.
In fact, in a recent report, it has been stated that 85% of artificial intelligence-based projects fail due to the lack of skilled personnel in the organisations. Hence, the shortage of experienced professionals with training became a critical problem for businesses who are willing to adopt artificial intelligence and transform their traditional business to data-driven models.
To break down this barrier, business leaders must bridge the technical gaps in employees by making non-technical people aware of artificial intelligence. Alongside leaders should also take this opportunity to upskill their existing employees which will help them fill the gap of skills shortage.
Keeping excellent communication with your technical team, to understand complex subjects like data science can be beneficial for organisations. Many companies also rely on AI-as-a-service solutions where people from non-technical backgrounds can also leverage the benefits of artificial intelligence without training. Also, several ed-tech companies have started AI courses for everyone where they are covering a complex topic of artificial intelligence for non-technical folks.
Create a company culture
There are many areas where artificial intelligence could be implemented to make a business impact, but CEOs and COOs still resist to adopt this technology in their business operations. One of the primary reasons for this is the company culture and mentality towards modernisation. Unable to change company culture for modern advancements can only be attributed to resistance to change. AI adoption is always a top-down initiative, and with business leaders getting comfortable with their traditional infrastructure, it gets challenging for the rest of the organisation to move towards digitisation. According to a report, only 26% of businesses have integrated artificial intelligence into their daily business operations, and only 6% of them have made it a primary resource for making business decisions.
Businesses can change technologies; however, changing culture can be a long process. Business leaders should start utilising data to make their day-to-day decision and should also democratise data for their employees to integrate it into their work process. Alongside, businesses need to create a common AI vision for their employees to set their priorities accordingly. Leaders should also encourage questions from their employees which develop a sense of trust among them and will also cultivate an environment of accountability. Organisations need to create a culture that welcomes AI business models and simultaneously empower people to leverage the abilities of artificial intelligence. Security also plays a crucial role in creating a comprehensive AI culture, where companies are working beyond compliance and obliging ethics in practising artificial intelligence.
Understanding responsible AI
To progress with artificial intelligence, there are a few things businesses should consider — ethics, privacy and responsible use of artificial intelligence. To understand the responsible use of artificial intelligence, enterprises need to understand the impact of their automation on the economy. With businesses busy managing artificial intelligence in automating tasks for their companies, they usually forget to consider the ethical implications of their automation. In fact, according to a recent study, it has been revealed that only 25% of organisations across industry consider the ethical implications of an AI solution before investing in it. Earlier this year, Vatican officials signed a pledge with Microsoft and IBM to promote ethical use of artificial intelligence for protecting the rights of the people. Here, the companies were aiming to increase awareness among companies and institutions to set a strict guideline to use this evolving technology.
Many governments have also created regulations and strategies around the usage of artificial intelligence for companies to deploy acceptable usage of this technology. Businesses should also create transparency in developing AI-based solutions for people, which, in turn, will develop a sense of trust in the solution. In a recent announcement, Google has shared a few best practices and a framework for the responsible use of AI within their organisation. This regulation will allow businesses and employees to trust AI-generated insights. To have an ethical usage of artificial intelligence business leaders need to formulate comprehensive AI strategies, develop a governance framework for data security, prioritise explainability, and create responsible AI applications that are significant to human development.
