The last few years has witnessed a boom in AI applications for business, covering everything from recruitment and HR, to customer insights and office management. Enterprise has, unsurprisingly, lead AI adoption, growing by 270% over the past four years. But that’s not to say AI is for industry giants alone. A ton of new AI apps offer companies unprecedented competitive advantage without requiring infrastructural overhaul. Here's our pick of the best AI applications for business currently available.
Dewo – for meeting scheduling and deep work
Dewo can completely automate meeting scheduling and minimize the productive cost of meetings themselves. Using AI, it considers your team’s productive patterns, timing preferences and calendar event distributions to find a meeting time with minimal impact on everyone’s deep work. It will also intelligently identify any existing meetings carving up your schedule and suggest a better time for them. It outsources all scheduling back-and-forth too – just tell it who you need to meet with and it will handle the rest.
EVA by Voicea – for documenting meeting actions
Eva uses speech recognition technology to capture audio information from meetings. By listening and transcribing meetings, it can completely automate minute taking. It ensures all details – such as meeting actions and decisions – are captured, and can even identify different speakers’ responsibilities. Its Conversations Inbox keeps all meeting notes in one central place – which is particularly handy for sending follow-ups and sharing information with anyone who missed the meeting.
Butter.ai – for sharing company knowledge
Butter removes the pain and faff involved with managing files across multiple work apps. With a mission to help people find the right document wherever it is, Butter is all about helping companies put company knowledge within easy reach of their employees. Just type in what you’re vaguely after and Butter will use AI to try and link you with the right file. Formerly a search assistant within Slack, it’s since been acquired by Box to transform search in their cloud content management service.
Timely – for automating time tracking
Timely automatically captures every tool you use for work and uses AI to translate your time data into accurate timesheets. It sets a new standard for honest invoicing, and ensures businesses actually get paid for all their work. Employees can review their time data down to the app they were using, to ensure all project work is represented – including commonly overlooked activities like internal team communication, travel, meetings and email. Free of timers and interruptions, everyone can return their focus to the work that matters.
Yva.ai – for supporting your workforce
Yva is an AI-powered assistant for employees, managers and HR departments alike, providing personalised insights and recommendations to keep everyone engaged. Employees gain a personal performance assistant that help keep employees on-task, while managers learn how to support employees better, improve culture and boost retention rates. Particularly useful to gauging your team’s engagement and predicting turnover.
Knowmail – for streamlining email
This AI-powered assistant works to simplify email management. It learns your unique email habits, patterns and preferences to provide personalized support everywhere you send and receive emails. Integrating with CRM and unified communication solutions, it helps you manage your daily email flow and identify what’s important.
AppZen – for self-auditing
AppZen is set to redefine how finance teams work, by using AI to audit all expense reports and invoices ahead of payment. Aside from validating prices, it promises to provide intelligent insights which help teams reduce spend, comply with policy and optimize processes. Integrating with all major back-office systems, it offers businesses the power of a super team of auditors without any disruption to their existing processes.
Legal Robot – for analyzing contracts
Legal Robot is helps to make stodgy business contracts understandable. Using machine learning, it compares thousands of legal documents to construct abstract representations of the language in a legal document. Aside from translating inaccessible legalese into plain English, it can also apply this knowledge to identify potential problems with a legal document, including its legal style, definitions and risky language.