What are real ways enterprises will consume AI?

Artificial Intelligence & Machine Learning (AI/ML)

83.2k views204 Upvotes64 Comments

Partner in Finance (non-banking), 51 - 200 employees

Many AI-based applications are finally making the jump across the hype cycle from ‘promising’ to ‘delivering’ real value. Chatbots are one that have made a dent in 2017 and will continue to do so in 2018. Messaging has proved to be a simple, and extremely effective way to communicate and interface with information. Message based apps leverage a commonly used medium to provide a conversational interface to complex workflows. This has already dramatically simplified how enterprise users interact with applications and collaborate at work, especially as more and more millennials enter the workforce with drastically different expectations for software than their prior generation.But adding AI to chat takes us beyond just simple question and answer commands. Instead of typing “File HR Ticket” to a SupportBot, an employee can simply describe their actual challenge, e.g. “what is our maternity leave policy?” Bots can handle complex NLP, decompose the question, search for potential answers across multiple applications/ backends, and instantly provide the user with the right answer. This greatly simplifies workflow and massively boosts productivity and customer/ employee satisfaction.Zooming out a bit, the bigger picture going into 2019 is very clear. AI will be built in as a layer across every application going forward — just as “mobile” used to be a standalone category, it is now seen as a necessary component of any software product.

18 2 Replies

Systems Engineer, Self-employed

From my point of view, I think that as people's needs grow, so do the technological options. From simple scenarios of problem solving with RPA, or just with ChatBots, etc. Currently, we can have more complex scenarios that demand the implementation of several digital tools that work collaboratively, giving the user-customer greater versatility when solving problems; in this situation we are talking about Hyper-Automation (HA). In summary, HA is a more advanced automation where it can include in the same scenario many technologies such as: RPA, Virtual Assistants, Cognitive Models based on AI, Process Mining, OCR, IDP, Advanced Analytics, IoT, etc..

Systems Engineer, Self-employed

UiPath, AA, Bluprism, Watson Assitant, Dialogflow, Node-RED, AutoML, KOFAX, etc, etc

WW Analyst Relations Manager in Services (non-Government), 10,001+ employees

For data validation and HCM replacement workers

President in Software, 51 - 200 employees

Through cloud services that seamlessly embed AI. Few will have anything of their own in the near term.

4 1 Reply

CTO in Software, 201 - 500 employees

Agreed. This seems like the easiest fore into the use of AI and the most practical route for the enterprises with low level of maturity when it comes to internal AI capabilities and considering the investment that needs to be made to bring this level up (by my estimation - most enterprises). Cloud services that operate over large quantities of signals/data (e.g., collaboration, data analytics, logistics, asset management, cyber security) present a perfect target for solutions providers to infuse those services with AI capabilities and the easiest way to consume them.

Co-founder & CTO in Finance (non-banking), 51 - 200 employees

In 2022, enterprises will consume AI in a variety of ways, including:
-Using AI to automate tasks and processes
-Using AI to improve decision making
-Using AI to develop new products and services
-Using AI to improve customer service
-Using AI to target and personalize marketing
-Using AI to improve employee productivity

7 1 Reply

CEO in Finance (non-banking), 2 - 10 employees

Spot on!

Director of Business Development in Software, 51 - 200 employees

Beside how essential automated operations and Informed Decision Making is important to enterprises, Enterprises are going more toward adopting a Customer-Centric Approach, with Machine Learning and Aritfical Intelligence they'll be able to show the care customers are looking for, that's what all the researches and studies showed in 2021/2022 that customers want businesses to care about them. Or else they would prefer to buy from those brands that do.

VP of Product Management in Software, 10,001+ employees

One of the biggest opportunities remains the chance for end user clients to self serve on their terms. Whether that's support, sales, research, or learning, AI can anticipate needs and deliver automated solutions and elegant on-ramps to human interaction. Chat GPT is a great example of where we're starting to see this taking shape.

https://www.cnbc.com/2022/12/13/chatgpt-is-a-new-ai-chatbot-that-can-answer-questions-and-write-essays.html

Senior Product Marketer in Software, 201 - 500 employees

I guess you mean 2023. Personally, I hope to see real AI getting into cloud resource management, so both savings and performance will be automatically optimized.

Director of Communications in Software, 51 - 200 employees

The best way to consume anything (assuming you have chosen to do so) is quickly, so that it can be absorbed and provide value. AI is no different, so decreasing the time-to-value is key. AI solutions or services that have long deployment timelines; or require complex integrations; or are just too ambitious in terms of skill-sets that organizations may lack will fail. So, time-to-high-value (don't think the phrase will catch on) AI that can be deployed and learn quickly is the nirvana. From our perspective (biased, of course) we think that using AI to automate customer calls is a ready-to-go way that enterprises can consume AI. Deploying a solution quickly to reduce customer call queue times; optimize call centre operations; and provide branded customer conversations to improve CX has got to be an attractive proposition, right?

Chief Executive Officer in Services (non-Government), 51 - 200 employees

Enterprises will use AI in many ways in 2023, such as: automated customer service bots, predictive analytics to anticipate customer needs, AI-driven product recommendations, computer vision for security and surveillance, automated scheduling and project management, AI-driven marketing campaigns, intelligent manufacturing and automation, AI-enabled analytics and insights, and natural language processing for customer support.

Group Head of ERP in Consumer Goods, 5,001 - 10,000 employees

I foresee the AI application in predictions about identifying areas of opportunity to increase profitability and reduction of operational cost.