The most valuable use cases for artificial intelligence in web applications – Information Age

The most valuable use cases for artificial intelligence in web applications image

AI is helping businesses use applications hosted online to their advantage.

This article will explore how artificial intelligence in web applications has been helping organisations drive value.

Web applications, stored on remote servers and delivered over the Internet, allow organisations to carry out tasks without the need to install products locally, while reducing costs. An array of different types of web application is currently available on the market, but one technology that’s really proved disruptive in this space is artificial intelligence. Capable of automating manual tasks, AI can lead to smarter decision-making using web applications, speed up operations, and bring other business benefits.

Matthijs Aler, CEO of Ohpen, believes the value that can be driven by artificial intelligence in web applications “is highly dependent on the type of web application”.

He said: “You can turn any successful machine learning model into a web application (such as Google Lens or Google Translate). At the moment the big breakthroughs are related to images and language, so web applications processing these are the most likely to be a valuable use case.”

In this article, we delve deeper into some of the most valuable use cases for artificial intelligence in web applications.

How data protection can benefit from artificial intelligence

This article will explore the ways in which data protection can benefit from artificial intelligence, as cyber attacks continue to grow and evolve. Read here

Overcoming the unstructured data challenge

While the structure of AI capabilities such as computer vision relies on unstructured data, many organisations still find it difficult to use asset types such as video and text to their advantage, with the sheer amount that’s out there often proving overwhelming.

Prashant Natarajan, vice-president, strategy and products at H2O.ai, commented that this challenge can be mitigated through web application projects carried out with the aid of open source.

“The most useful applications of AI in web applications span across the entire enterprise on one hand, and across multiple verticals on the other hand,” said Natarajan.

“Today, any web application that deals with customer experience, employee experience, enterprise resource planning, or going down to the supply chain, HR and talent management, privacy, and governance — these are all business processes where AI is being applied today.

“If you are confused by where to start your AI journey, interestingly, the lowest hanging fruit for getting a proof of concept going is in the toughest class of data that we have had a challenge within the enterprise — unstructured data. All that mass of documents, text and images used to be a black box for organisations, and estimates are it could be as much as 80% of all your corporate ‘memory’. But with today’s AI and ML technologies, and the knowledge you can access in the very rich open source AI community, you might be amazed at what you can achieve.

“Personally, I find it fascinating, and grounds for optimism, that what has historically been our most difficult information problem might be the easiest one to start a great web application project on, today.”

AI engineering for cloud applications

With many web applications utilising cloud infrastructure, AI engineering can be tailored to suit the needs of the business, and prove key to quickly delivered, actionable insights. From here, this use case can make access to AI-powered tools easier for staff who may not have a background in tech.

Amir Hashmi, CEO of zsah, explained: “AI engineering is a critical enabler to adapting cloud computing technology to our needs. Cloud services enable users with low skill sets and limited budgets to access advanced machine learning functions.

“With more AI engineering, cloud computing will make advanced toolsets more widely available, leading to improved organisational efficiency and productivity.”

How to leverage AI and automation for cloud migration success

In this article, Rob Duffy, head of solution development at Cloudreach, explores how to leverage AI and automation for cloud migration success. Read here

Aiding collaboration

Notably, the pandemic saw a surge in usage of web applications, in the form of collaboration software that can be accessed online. With the aid of AI, use of these platforms can become more efficient.

“Hybrid working has dramatically shifted the need for AI to improve the ways in which we can know our customers and employees,” said Nick Atkin, head of solution architecture at Dubber Technology.

“By signalling trends in both – sentiment, tone, keywords and more – across millions of conversations, AI increases the ability to end not knowing. AI will drive a transformation in people, customer, revenue and compliance intelligence.

“The continued integration of AI into every way we communicate – Cisco Webex, Microsoft Teams, Zoom, mobile and chat applications – will change the way we use these methods. Not only do these platforms get better, but we also change the way we use them.

“Every meeting can be automagically captured and transcribed – then topic, actions, highlights, keywords automatically generated. Imagine the power of not just meetings that were impactful, but taking back hours a day by eliminating manual note taking and not attending meetings you only need to review at a later date — or instantly providing transcribed and audio context to a team member you need to take on a task.”

Combinations with IoT

Colin Crow, UK managing director at Nexer, added that AI, combined with the Internet of Things (IoT), can be particularly valuable across various sectors, when it comes to using those all important data insights.

“Today, the most valuable AI structures for web applications will be combined with IoT and visual search, and will add value in many areas,” Crow said.

“Field service is using AI to predict maintenance schedules, with schedules now based not on time between service but on the likelihood of degradation, significantly reducing service costs, lowing spare part costs and ensuring a higher uptime.

“Retailers are using AI and visual search to accurately determine shoe size, so that when a shoe is ordered the system determines your size and not you. Thus you get what you like first time and return costs (which equate to around three in every one purchased) are drastically reduced.”

Spread the love

Leave a Reply

Your email address will not be published.