How Can Artificial Intelligence Boost Your Business Productivity?

Artificial intelligence has already become a noteworthy business buzzword. We all have experienced the influence of AI on our daily lives by using Google’s predictive search, learning about the weather from Siri, or Alexa playing our favorite music. However, these examples are only scratching the surface of possibilities carried by Artificial intelligence for business. Artificial intelligence in the business context saves time in carrying out routine administrative tasks, along with providing tools and innovative ways to increase customer satisfaction and expand the customer base. Implementation of AI for business is cost-effective, integral to customer engagement, and appropriate for mitigating the lack of skilled personnel in an organization. According to Accenture by 2035, Artificial Intelligence will increase business productivity by 40 percent or more. 

Let’s discuss the current state of AI in business, the reasons why entrepreneurs should use the technology, its benefits, and how to adapt it for your business. 

Outlook on Artificial Intelligence

Artificial intelligence is the collaboration of a variety of tools and technologies that are equipped for sensing, recognizing data, extracting visions, and executing tasks based on the knowledge obtained. With the ability to learn from data and modify it over time, it is seen as one of the most effective solutions for powering business processes and making autonomous decisions. The accumulation of large amounts of data collected from users through social media, education, eCommerce, and other platforms, and a deeper understanding of how to use this data generated strong demand for smart Artificial intelligence systems. Machine learning, knowledge-based systems, and natural language processing are some of its topmost executions today.

Knowledge-Based Systems

Knowledge-based systems or expert systems are some of the most accepted and probably the most effective AI systems for business. As a subset of knowledge-based systems, rule-based systems make use of the procedure earlier demonstrated by experts to offer support in making difficult business decisions. These systems have the ability of human experts. Newer versions of expert systems also contain probabilistic relations, such as between origin and effect, increased by causality and progressive relationships as well.

Natural Language Processing

Natural language processing (NLP) is a crucial AI technology for business operations these days. In their simplest form, these systems offer consistent translation in a defined context. Business applications of NLP are numerous, from solutions for an internal association to database searches, from content management to online customer support to e-Commerce.

Most implemented business applications of NLP consist of content and link analysis of web pages, extraction of particular information from texts, and automatic classification. Natural language processing uses techniques to transform unstructured data from text, audio, and video sources to structured data that can be used by decision-makers.

Machine Learning

Machine learning is a group of computational algorithms that can process huge amounts of data quickly. This technology leverages learning as a dynamic procedure, and the algorithms can get better at what they do, the more often they do it. One of the most incredible machine learning techniques is deep learning. Deep learning is the combination of various networks capable of learning from unstructured data. Deep learning algorithms have become very effective and precise due to the large-scale availability of business data and the rise in available computing power.

Artificial intelligence is disrupting existing business models and building new ones in many businesses. According to PwC’s research AI will have a US$15.7 Trillion prospective contribution to the global economy by 2030 and up to a 26% enhancement in GDP for the local economies. The main advantages of artificial intelligence and machine learning are scalability and constant improvement abilities. In terms of business, these benefits will increase corporate productivity, lower costs, decrease human error, and generate an expanding and competitive advantage for enterprises.

Reasons Why Business Entrepreneurs Should Use Artificial Intelligence

Businesses can utilize AI technology to accomplish strategic purposes in figuring out what was wrong with their policies in the past, making predictions about what will happen in the future, and setting plans on how to accomplish better results. There are five reasons why business entrepreneurs should use AI.

Access to Information

Artificial intelligence solutions modernize the procedures of identification, recovery, and utilization of information across the whole enterprise. Timely access to the correct information is important for making informed and collaborative choices that impact business outcomes.

Creating Insights

AI-based business tools can reveal hidden insights in data. Insights are important for a detailed understanding of cause and effect relations within a business perspective. Having access to the most valued insights helps business entrepreneurs make improved decisions that enable profitable and sustainable growth.

Business Foresight

Artificial intelligence technology can help enterprises leverage data from the past to predict future results. Business foresight capability can anticipate the modifications early on, advise the best course of action to meet business necessities, and ensure the long-term existence and success of the company.

Commercial Agility

Utilizing AI can help businesses increase their ability to quickly adjust to the changing market and environmental situations while maintaining productivity and keeping the expenditures to a minimum. Lately, organizations around the world have started using cloud computing, enterprise architectures, business-IT alignment, and context modeling to grow their business agility. Artificial intelligence acts as the binding material for these approaches while accelerating the company’s real-time decision-making.

Strategic Alignment

AI works as the linking mechanism in business – from strategy to execution. Data-driven AI alignment inspires the establishment of business strategies for escalating the performance benchmark of its processes. At the same time, AI can increase enterprise and operational visibility and associate them with preferences, priorities, aims, and requirements in a business context.

Benefits of AI for business

Artificial intelligence in business includes a set of computational tools and techniques that allows organizations to gain actionable insights from data, which, in response, boost productivity, reduces costs, increases revenue streams, and accomplishes corporate, social, and economic goals.

Improved efficiency

Machines and tools powered by artificial intelligence can outperform people in specific tasks, work round-the-clock, don’t take breaks, and don’t have issues with concentrating. They can support your business 24/7 and reply to significant events at the right moment or answer customers’ requests.

One of the main benefits of AI is its ability to evaluate large datasets very quickly as compared to long hours or days it would take a team of human experts to complete. Artificial intelligence can also perform tedious tasks and automate work routines which are most useful for small business owners.

Competitive Advantage

Data is the new fuel that needs to be processed to make it valued for the current digital economy. Enterprises can utilize AI to instantly crunch huge amounts of data and get better answers to questions appropriate to their domains. For example, a digital content writing company might need insight into what movies their customers desire and make exact predictions on whether customers might cancel the subscription. Artificial intelligence can offer these forecasts with comparatively high accuracy based on past and contextual data.

Insights mean a competitive benefit for businesses, allowing companies to produce better products and facilities for their customers, reduce the risk of failures, reduce costs, escalate operational efficiency, and increase safety and compliance.

Mitigating Mistakes

Artificial intelligence is not prone to mistakes preceding human opinions or emotions. However, AI sometimes may form unfair decisions if the dataset does not correctly represent the whole population or a variety of cases. For example, Amazon once scrapped a gender-biased AI recruiter tool that selects mostly male applicants from a pool of CVs submitted over years. The problem was that the CVs in the dataset came mostly from men.

Enhanced Customer Experience

AI solutions for enhancing customer experience include using their behavior data to offer products or services that are more engaging to them. For example, the marketing department can predict how select customer groups may respond to their promotion message. By evaluating how customers talk to each other, an AI chatbot can recommend phrases and moods that are the best fit with a section of the users. The data about customers, their location, favorite products, and social activity can help businesses provide more appropriate products and tailored experiences.

One of the best use cases of AI for enhanced customer experience is Netflix’s recommendation engine that is modified and recommends movies based on specific preference. Similarly, Amazon’s Alexa assistant helps organize shopping lists, generate music playlists, send emails, and find basic information. In the travel industry, standard AI solutions are available to customers 24/7 in real-time to recommend personalized vacation packages and give updated information about their scheduled itineraries.

How to Embrace AI into Your Business

Artificial intelligence has the outstanding potential to reform business in every sector of the global economy. In the present state of Al ML development services, companies need to make crucial but perceptive decisions and quickly react to the potentials and risks that go hand-in-hand with digital transformation. While there is no final recipe, the five features below are key for attempting AI integration.

Recognize the Right Business Use Cases

The most basic and essential step in implementing AI into an organization is to recognize the business use case that has the maximum value potential and to align it with the company’s policy. This step involves the identification of realistic capabilities, accounting for the restrictions that AI has in a particular real-world scenario. Recognizing the right business use case is a knowledge-intensive component of AI transformation because it needs expertise in both business development and the inner workings of AI technology.

In the short term, it is advisable to create use cases that have proven scalable AI technology resolutions such as robotic process automation or specific applications of machine learning. For the medium-term, companies can select use cases using AI technologies that haven’t been recognized as scalable yet. For the long-term, companies can choose use cases with unverified AI technologies that will have a high influence and partner with researchers or third-party companies that focus on the growth of AI solutions.

Build up Your Data Ecosystem

Data is a crucial business asset for corporations that want to join the AI revolution. AI algorithms need large volumes of data for working out that often come from various systems and sources in different formats. Companies should find the sources of their data, build infrastructure for its storage and handling, anticipate the expenses related to the collection, embrace the risks of incorrect data, and develop strategies for obtaining additional data appropriate to their business operations.

The benefits of data ecosystems become obvious when companies expand the types of data they gather and store. Generally, one type of data can become suitable only when combined and evaluated together with the others. For example, the combination of customer sentiment with real-time event geo-data can give business uniqueness and exceptional customer experience to any brand.

Develop Your AI Proficiencies

The internal proficiencies to develop the preferred AI solution are the foundation of an effective transformation. Only organizations with the right experience will be able to capture the real value of artificial intelligence. Companies need to hire AI ML developers to design, implement, deploy, troubleshoot, retain, and progress their AI advantages. To develop the complete range of abilities, companies may need to partner with external solution providers that have a particular skill or give some of their key operations to other service providers. An agile development approach is crucial for companies to move quicker through the test and learn cycles.

Integrate AI into Your Business Workflow

Running AI solutions at scale and getting satisfactory outcomes is only a character part of the story. To fully capture the advantages of the use case, businesses must reform business processes and integrate the results into their workflows. Sometimes integration may include automation, and other times it needs designing channels so that the right data insights reach the right people inside the company.

The integration of AI insights into the business workflows involves re-thinking and reorganizing human-machine interfaces. A clear distinction is required to distribute tasks between company staff and machines. In an AI-driven world, many job descriptions will need to be reviewed and restructured.

Train Your Employees

Implementing artificial intelligence into the business process needs lasting organizational changes. The standard of human-machine collaboration is comparatively new, and the workforce requires to be explained and implemented to this mindset. Businesses must offer education about the opportunities and challenges of this paradigm to adopt new types of associations. Training the employees may take time, so building an AI-ready company culture should come initially on in the transformation. Special attention should be devoted to the education of mid-level managers on how to use data-driven insights in their management process.

Conclusion

Implementation of artificial intelligence transformation in business is not an easy task. Companies need a structured approach that initiates with recognizing business use cases with the maximum potential. They need to develop data ecosystems to ensure the success of AI algorithms. At the same time, companies need to encourage various abilities and find ways to integrate AI results into their workflows. Therefore it is advisable to gain the preferred capabilities by offshore AI developers and Machine Learning & Artificial Intelligence Experts from leading AI development services providers such as Explorate Global.

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