Why Implement AI into Your Business Model Sooner?
Technological progress within the area of AI has led to increased interest among a wide range of businesses. According to the Artificial Intelligence Global Executive Study and Research Report (Ransbotham et al), 90% of the respondents revealed that AI offers opportunities. However, 40% of the respondents reported that significant investments did not result in business gains. Barriers to the successful implementation of AI are associated with the technological, cultural, and political domains. However, strategic considerations are vital as technological improvements do not ensure success when implementing AI applications. This highlights the importance of well-structured business models (BMs) to adapt and capitalize on existing technology assets. AI is instead considered a catalyst for BMI and is thus also an enabler for the disruption of industries.
The process of value creation is one of the main segments of business model innovation (BMI) that is connected to AI through its ability to solve complex problems based on large data-sets. BMI unlocks the potential to refine or expand current product portfolios and operate more efficiently to cut costs.
Digital strategies are instrumental when transferred to digital business by taking into account relevant systems and corporate infrastructure. Data acquisition and data infrastructure are crucial to ensure a sustainable design that promotes AI operations. Large data sets and data analytics, or big data, is often referred to as the fuel that enables the AI-algorithm to produce its result. This implies that the data amount and quality will directly correlate with the output. Thus, qualitative data sets constitute a precondition that is required to succeed with AI initiatives. The principles of lean startup methods can be applied as a potential strategy when building and developing robust data infrastructures. This method is based on the concept of minimum viable products, continuous data collection, testing, and refinement. Hence, this strategy will form a virtuous cycle of AI. The technology can also deliver a substantial qualitative change to business organizations and create new opportunities for company growth.
According to PwC’s report, “Bot. Me: A revolutionary partnership”, 67% of executives believe AI will help people and machines work together to improve operations — by combining artificial and human intelligence.
Moreover, PwC’s analysis suggests global GDP will increase by up to 14% by 2030 thanks to the ‘accelerating development and adoption of AI,’ which means a $15.7 trillion boost to the economy. But what are the driving forces of such growth? On the one hand, an increase in business productivity, on the other, an increase in consumer demand, driven by better quality and increasingly personalized AI-enhanced products. It’s hard to deny, AI is the future of business, and sooner or later, the majority of companies will have to implement it to stay competitive.
Furthermore, according to Harvard Business Review’s survey of 250 executives who are familiar with their companies’ use of cognitive technology shows that three-quarters of them believe that AI will substantially transform their companies within three years. Also according to the same survey, the benefits of the AI tech in firms are as follows:
Consequently, it can be said that the benefits of artificial intelligence for business models are:
- Increase employee productivity by, automating routine tasks and processes.
- Improve marketing activities by, generating content that reflects client needs.
- Save time and money by, replacing manual systems with automated software.
- Avoid human error stemming from complex mathematical equations and analysis.
- Achieve the best business results thanks to insights that predict client needs and allow companies to deliver personalized solutions.
- Maximize sales opportunities and increase revenues.