If there's one technology that most organizations include in their strategic roadmaps, it's artificial intelligence (AI). According to the prestigious digital transformation consulting firm Gartner,”70% of organizations will have implemented operational AI architectures due to the rapid maturity of AI orchestration initiatives“by 2025. Likewise, Forrester foresees”that one in five organizations will double their investments in AI“.

So what are the common business scenarios for AI applications? How will it gradually change the daily life of businesses?

Multiple factors in today's business environment are driving organizations to accelerate their plans with AI:

• Business applications are migrating to the cloud, allowing businesses to seamlessly access required data.
• Machine learning (ML) models ready to use are operated by platforms Low-codeor No code, which leads to a strong democratization.
• We also observe advancements in complementary technologies in sectors where AI promises significant benefits:

5G is disrupting the telecommunications sector

• The Internet of Things (IoT) influences the manufacturing, automotive, and oil and gas sectors
• Omnichannel experiences boost the retail and e-commerce segment
• The blockchain influences financial services, purchasing, logistics

So AI is not a magic solution that can be deployed in the same way in all businesses. Organizations need to understand the underlying core functional capabilities that AI can help develop.

5 scenarios where AI can help you

• Interpreting documents

As the name suggests, in this scenario, AI helps businesses classify and extract information from unstructured documents. As the maturity of machine learning models evolves, businesses can gain greater accuracy and confidence while extracting data with fewer data sets.

• AI computer vision

Computer vision makes it possible to interpret elements on the screen with recognition similar to that of a human being. This allows businesses to create vision-based automations that can work in most virtual desktop interface (VDI) environments, regardless of the framework or operating system.

• Natural Language Processing (NLP)

An NLP capability helps with language detection, unstructured data extraction, and sentiment analysis. Exploring communications is the application of NLP to commercial communications. It extracts intent data (like customer issues and reasons for contact), tone, and feeling in order to automate and understand business processes.

Email automation is one of the main uses of communication exploration:

• Extracting emails from underlying systems
• Classification according to target scenarios
• Extracting information from the respective email (unstructured)
• Information processing as required (such as creating a ticket in ServiceNow)
• Predictive analytics

With access to historical data, machine learning models allow businesses to make more informed decisions. In fact, they use this capacity to better predict demand, offer personalized offers, predict network failures, fraudulent transactions, etc.

The industries of the future for AI

• Banking and financial services

Forrester predicted that AI would be one of the main technologies that”Would banks win in 2022“ . “Interest in AI, microservices, and analytics remains high. Overall investment levels vary, but in particular, budgets for AI and machine learning are high“.

• The pharmaceutical industry

According to a McKinsey report, the use of AI technologies improves decision-making, optimizes innovation, improves the efficiency of research and clinical trials, and creates new tools that are beneficial for doctors, consumers, insurers, and regulators.

• Telecommunications

According to experts,”The size of the global market for AI in telecommunications“should grow”at a CAGR [compound annual growth rate] of 42.6% during the period 2021-2027“. This evolution is largely influenced by the adoption of 5G technology by service providers, resulting in net new use cases for the business-to-business (B2B) and business-to-consumer (B2C) segments.

• Computing

Chief Information Officers (CIOs) are recognized as the torchbearers who are driving the adoption of AI across businesses. As far as IT is concerned, two aspects must be taken into account. First, IT managers use AI for their internal functions to optimize IT operations, run a touchless help desk, etc. Second, IT teams promote best practices in AI to businesses, which promotes the adoption of AI with minimal risks.

• Human resources

According to a 2020 Gartner article,”17% of organizations are already using AI-based solutions within their HR function“ . “HR leaders cite cost savings, accurate data-based decision-making, and improved employee experiences as top reasons for deploying AI“.

About StoryShaper:

StoryShaper is an innovative start-up that supports its customers in defining their digital strategy and the development of automation solutions tailor-made.

Sources: StoryShaper, UiPath, Forrester, Gartner, McKinsey