The Rise in Using Artificial Intelligence (AI) to Support Business Decision Making
Breakthrough in the fields of Machine Learning and Deep Learning have allowed businesses to leverage Artificial Intelligence (AI) technology to analyze vast amount of data to extract valuable insights in ways that was thought to be impossible before.
While tech powerhouse like Amazon, Google, and Facebook, as well as other big corporates have long been using the advanced technologies of AI and machine learning to optimize and streamline their business processes, many other businesses are still trying to assess whether it’s worth investing in AI to acquire the advanced solutions solving key business challenges, and support business decisions making to boost productivity and profitability.
In 2019, it does not cost a fortune to adopt AI technology like how it used to be a few years ago. AI’s advanced capacity to automate a numerous repetitive tasks make it the ideal solution for performing a range of job duties which eliminate the majority of human involvement. In fact, a competitive advantage of AI today is how cost-effective it has become so that even SME (Small and Medium Enterprises) can now harness the power of AI without having to spend a fortune to afford it.
AI solutions development, done well, can enhance business decision making and transform the ways many business activities are done. In this article, we look into how AI development can support business decision making, for better outcomes and improve overall efficiency.
AI – Why is Artificial Intelligence Necessary?
AI solutions development seeks to automate various cognitive and physical tasks, reducing human effort for other activities which require more attention. Moreover, AI provides actionable insights to support executives making better and profitable business decisions. There are many ways in which AI has been used to optimize business process. With large amount of data becomes increasingly more available, AI and machine learning technologies can process and analyze those data to find hidden patterns, enabling sales teams to identify the highest potential new prospects to prioritize on them saving sales team a lot of time and effort. This gives business organizations the opportunity to increase sales revenue with algorithms.
The primary purpose of adopting AI development is to gain a competitive edge in the new digital economy, whether it’s retail, manufacturing, healthcare, or finance etc. AI technology has the capacity to help businesses boost productivity, increase sales and reduce overheads, automate and enhance customer services tasks, reduce performance errors, together with data capture and processing. In the coming years, the world is expected to see the immense effect of AI in enhancing the economy with more efficiency and capacity. An Accenture research shows that AI has the potential to boost rates of profitability by an average of 38 percent by 2035 and lead to an economic boost of US$14 trillion across 16 industries in 12 economies by 2035.
AI involves multiple technologies that can be put into used together in different ways to sense, comprehend, act and learn. Gartner forecasts that, in the year 2021, AI Augmentation will create $2.9 trillion of business value and 6.2 billion hours of worker productivity globally. Also, according to the same Gartner article, it is predicted that, by 2030, decision support/augmentation will be expected to surpass all other types of AI initiatives to account for 44% of the global AI-derived business value.
With such strong predicted figures, AI is likely to become the most suitable technology choice for both SMEs and Corporates in order to support their business making process. AI can help assist the progress of both economy and human’s everyday lives.
Today, along with the innovation of cloud computing enables business to store vast amount of data at a very economical costs, AI and machine learning technologies can help extract insights out of those data to help optimize various business process. AI can help alleviate or avoid the costs of making the wrong decision by excluding human bias and “guess-work” when making decision. As mentioned in previous blog posts, today’s AI system usually starts from scratch and developed and train based on a regular feed of big data. Let’s examine the following business areas where AI can make an impact in support to make business decision.
Examples of AI to support business decision making
Marketing with AI
In the today world of customer centric economy, businesses organization need to have a thorough understanding of their customer needs and demands, in order to match those needs with the appropriate products and services accordingly. Thus, being able to predict the consumers’ needs and/or change in demand will prepare business to make effective business decisions, in the short and long-term.
AI and machine learning techniques offers actionable insights which could help companies predict customers’ behavior and make appropriate decisions to automatically address their needs in real-time or in-advance – retaining customers before they stay away and turning to competitors.
Customer Relationship Management (CRM)
CRM system with AI enablement (e.g. Salesforce Einstein analytics) provides many advantage for business organizations such as: end-to-end customer insight, and historical analytics to help agents plan for their next actions better and more effectively. Machine Learning modeling can also provide companies with a forecast of a customer’s lifetime value.
Sales Forecast
Employing machine learning model to analyze the aggregated data related to past sales activities, companies can improves the accuracy of their sales forecast for better planning and execution. This is particularly useful when companies need to forecast demand for the sales of their new products and/or services where they do not have much experience in doing so, AI can helps business reduce investment risks in launching new market product.
Sentiment analysis to derive audience insights
Sentiment analysis offers companies a better insights into how the audience perceive their brand as a whole. Gaining understanding of the emotion behind social media posts helps businesses to better respond and proceed with their upcoming marketing content and businesses agenda.
For many b2C businesses where customers review play an important role in affecting success, sentiment analysis can assist customer service representative to make better decision and properly address negative reviews and monitor dissatisfaction before it turns into a wide-spread problem.
Fraud detection at scale
In the past, checking credit card transactions to determine fraudulent activities were done by operators manually. With AI capabilities, financial institutions can now apply Machine Learning techniques to determine potential fraud transactions and, thus, be able to build their own fraud detection systems in real-time that can take very quick actions to stop those fraudulent transactions in a systematic way that is more efficient than manual checking.
Considerations
Regardless of what your businesses try to achieve from AI, it’s important to remember that AI should be leveraged to support users’ experience. Using AI to support decision making must fit with the organization process and workflows, and comes in the forms that make sense for users. Thus, an AI solution development endeavor should take into considerations of user interface, workflow design, and business analysis.
Also, your organization may consider partnering with a technology partner who already has a track record of experience working on AI design, and development as a proven method to avoid many potential AI development challenges and improve project success. A reliable technology partner will possess the necessary technical and domain knowledge to help your business making use of Artificial Intelligence (AI) in decision making. They will also provide you with advice on how to acquire the needed data and management of such data.
Conclusion
All the buzz surrounding AI in support of decision making might make business leaders think that they could pilot their organizations automatically and things will fall into place. In practice, implementing any AI initiative takes time and effort, it requires a long-term vision and strategy together with a realistic understanding of the technical challenges and data involved.
Business leaders, therefore, should understand all the implications and requirements surrounding the use of AI before embarking onto adopting it. However, thorough planning and partnering with the right technology service provider will help business achieve their AI goals in a systematic way. In the new economic landscape where experience and common sense are no longer sufficient to assess the risks and consequences of critical business decision making, AI and Machine Learning can support business decisions making, lowering risks involved considerably driving businesses to better success.
