As we begin the 2020s, Artificial Intelligence and Machine Learning are everywhere. We hear about them all the time and for some of us, they bring to mind ultra-specialized, even unobtainable technologies. AI is becoming part of our day-to-day lives, as well as being particularly important in industry, notably for large projects such as driverless trains and cars and managing road or even air traffic.
In the professional world, AI has become an asset for most departments: it might require a lot of technical expertise but it is everywhere!
Artificial Intelligence and customer service
You have probably already used one, to contact customer services for example, because these tools are developing at breakneck speed. Chatbots are conversational agents ready to reply to your questions at any time, day or night. You can find them on Facebook Messenger, WhatsApp, Twitter and Slack, to name but a few.
80% of companies will use chatbots for customer service by 2020
While some chatbots simply follow a decision tree to answer recurring queries, other are real conversational agents we can write to, who identify the issue and reply in natural language. These self-learning conversational agents improve as they interact with customers, a feat rendered possible by machine learning.
So, chatbots are a good way to maintain high levels of customer satisfaction, since Gartner predicted that in 2020, 80% of customer service interactions will no longer be human. Things may be going automatic quickly, but this should not become a source of frustration for customers: how many times have you found yourself stuck with a voice saver which can’t deal with your issue? Even without human interaction, customer service should be seamless and effective, and it’s here that Artificial Intelligence really comes into its own.
Beyond these intelligent conversational agents, artificial intelligence also helps companies to solve client problems and accelerate processes: this is how some bots like Salesforce’s Einstein allow for task automation on a CRM platform. Once they are up and running, this type of agent could also deal with other types of request. For example, AI is beginning to be used to automate product returns and exchanges.
Digital giants such as IBM, Salesforce and Amazon Web Services are tuned in to these trends and offer cloud-based bots, but similar technology is also provided by many startups and independent businesses, who develop bots for companies.
AI supporting business performance
Over and above knowledge and client management, AI also helps companies improve sales performance and the impact of marketing campaigns. Online sales players are well aware of this and have thus created extensive personalized search mechanisms. Amazon has even filed for a patent for a predictive sales algorithm: “predictive shipping”, whose objective is to deliver products to customers that they have not even purchased yet, based on their previous purchases.
In marketing, AI is not only reserved for the biggest market players. Big progress has been made and democratized: thanks to techniques like “computer vision”, numerous e-commerce sites are able to propose shopping suggestions based not on key words consumers are typing, but on images of products they have viewed. Thanks to these image recognition technologies, numerous online sales players can thus improve their offer, and increase their clients’ average spend.
AI also supports companies in their digital campaigns, especially when it comes to targeting users. Have you ever asked yourself how to define very precise targeting criteria to reach prospective clients on social media? This is a question on which social media players have reflected, and to which they’ve responded thanks to AI: their algorithms are capable, thanks to information collected from your consumers, to establish “twin consumer” profiles so that you can target leads related to your clientele and count on a strong conversion rate.
In brief, with AI, you can determine who your clients are and what they want, as well as identifying future clients.
AI in companies is also a good way to improve follow-up on your performance: its algorithms process large quantities of data and allow you to identify trends, giving you valuable insight. A great tool for marketing, and also for other support functions, like finance for example.
AI in companies: a real financial asset
In finance, AI is mostly the prerogative of larger organizations since its implementation can involve huge investments. Nonetheless, numerous fintech startups are enjoying the benefits of AI’s progress; the technology can also monitor and analyze data.
Fintech companies, whose work links finance and technology, are already widely known by the public for simple apps: crowdfunding, money transfers between friends, money management etc. But more complete services which rely on AI are also burgeoning. Fintech players are developing increasingly powerful AI-based algorithms. By processing large amounts of data and predictive models, such processes as financial reporting, asset management and loan granting can be automated.
Within your finance department, AI can thus improve numerous processes. You can turn to suppliers to move towards algorithms for automatic debt recovery, independent competitive intelligence or predictive analysis. Other apps involve fraud detection or internal accounting. Thus, you can achieve better efficiency and concentrate on high added value tasks. The end goal? Benefit from a better economic intelligence and therefore make better informed decisions. From asset management to investment decisions, finance can also benefit from AI in companies.
Big projects made accessible to small organizations
As we have seen, it is not only large companies who can benefit from AI-based algorithms. Nor is it necessary to invest huge amounts in a dedicated AI department. Anyone can call upon external providers to develop AI-related projects. This can bring gains by automating time-consuming or low added-value tasks. Nonetheless, as with all internal change, launching AI-based tools requires real support as well as commitment from the teams who will use these functions in their day-to-day work. The goal is that all players get on board with the project and that external providers, whether they be large companies or freelancers, integrate into your organization’s structure throughout the project. This is how you can ensure the successful implementation and efficient use of AI-supported technology.
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