The fast-paced world of Artificial Intelligence (AI) was once confined to science fiction books and movies, but in today’s era, it is transforming the real world in rapid fashion. The emergence of AI, from education to healthcare to the home, has become inseparable from our daily lives.
With current technological advancements, artificial intelligence is also reshaping the landscape of the business community. The rise of intelligent innovations enables businesses to work efficiently by streamlining operations. Under the umbrella of artificial intelligence, emerging technologies such as machine learning, deep learning, robotics, natural language processing, computer vision and cognitive computing contribute greatly to developing hyper-automation with high-degree precision.
In this article, I'll go through the following topics:
- Top AI Companies
- Machine Learning Services Offered by Top Trending AI Platforms
- Top AI-Employed Industries
- Use Cases of AI/ML in Business
- Business Management
- Business Analytics
- Marketing & Sales
- AI in Health Care
- ML-Enabled Crowdbotics Services
Top AI Companies
In the business world, the infusion of AI capabilities into business models and strategies has resulted in better interoperability, high availability, sustainability, and competitiveness to withstand global market fluctuations. The top AI companies in terms of impact on the global market include Google, Apple, IBM, Amazon and Microsoft. These "tech giants" keep up with developing AI via the acquisitions of startups; the number of recorded acquisitions for each (per arxiv.org) is shown below:
- Google: 37 acquired ML startups
- Apple: 25 acquired ML startups
- IBM: 21 acquired ML startups
- Amazon: 19 acquired ML startups
- Microsoft: 16 acquired ML startups
According to CB insights, the growth of artificial intelligence acquisitions has exponentially increased in recent years, with 635 AI acquisitions since 2010 and 166 in 2018 alone.
Machine Learning Services Offered by Top Trending AI Platforms
The top AI companies offer the following fully-managed machine learning cloud services, which can be employed as ready-to-use models and incorporated within business environments:
There exist numerous real-world applications of AI-driven systems and AI agents in day-to-day processes of organizations. The top industries where AI is maximally employed are:
- Business intelligence
- Core AI
- Marketing & sales
Use Cases of AI/ML in Business
Within the industries listed above, AI agents are used to streamline operations. The goal is to optimize efficiency, enable data-driven informed decisions, and automate the business processes.
Here are some of the common business use cases.
The core value of all businesses is maintaining customer relations. Artificial Intelligence helps businesses with external relations in the form of smart virtual assistants, popularly known as Chatbots. They provide AI-powered conversational interfaces for online customer support.
Chatbots are capable of human-like conversation with the customers by using textual and auditory methods from natural language processing algorithms. These intelligent agents allow almost-immediate personalized responses to customers by reducing delays as well as eliminating human errors. Amazon’s Alexa, Google Assistant, Microsoft's Cortana, and Apple’s Siri are the most commonly used voice-based agents that are successful in understanding context and processing of low-level queries in an efficient manner.
Some successful implementations of chatbots include:
- Google Duplex - For making real world calls
- 1-800-Flowers - For placing orders of flowers
- North Face - For product selection
- Spotify - For discovering weekly playlists
- Endurance - A companion for dementia patients
Aside from chatbots, AI is also used when emailing. Today’s businesses depend on infrastructure with advanced utility features, and emails are considered the most significant applications used for daily communication.
AI is contributing marvelously in automating workloads; smart email categorizations are being done by fast machine learning algorithms to manage huge influxes of data and automatically prioritize and route service requests. Automatic forwarding rules reduce the overhead of bulky data management, hence enabling smart replies. Gmail, offered by Google, and Outlook, offered by Microsoft, are two major products possessing smart functionality.
Business analytics refers to the processes that identify trends and patterns in data to optimize business processes and enable data-driven, informed decisions. Business analytics plays a vital role in almost every aspect of business, from business reporting to data warehousing to data mining to optimization. There are many business analytics tools with cost-effective features for predictive analysis and enterprise performance assessment, such as Microsoft's Power BI, Amazon's QuickSight, and IBM's Analytics Engine.
The most promising ML-enabled business intelligence app is HANA - SAP's Cloud Platform, which is being used by organizations (like Walmart) to process high volumes of transaction data in a matter of seconds. It is enhancing operational efficiency with a significant reduction in cost. Transaction records can be observed with HANA to highlight real-time trends and fluctuations in data in order to determine future actions.
Similarly, DOMO, an integration of predictive analysis, AI, and machine learning, facilitates data extraction and data analysis from multiple sources (like Shopify, Facebook, and Salesforce) to support deep insights and derive useful predictions. DOMO is currently employed by companies such as MasterCard, Univision, eBay, the Honest Co., and SAB Miller – these companies hope to boost performance with DOMO's help.
With the proliferation of technology, privacy and data protection have also become main concerns.
AI-based agents can detect fraudulent activities and protect organizations from cyber threats by recognizing and inspecting unsafe risks across an enterprise network without human interaction. This is done by using machine learning approaches to carry out behavioral analysis for the detection of anomalies to ensure data security on business networks. AI-backed multi-factor authentication methods are one popular way to protect against virtual threats.
AI-Squared, a collaborative effort by MIT and PatternEx, predicts security breaches by processing and analyzing a bulk of data produced by users to identify odd activities. Similarly, DeepText, a deep learning-based text understanding engine developed by Facebook, targets the elimination of online hate speech and filters spams to enhance user experience. Google also supports spam filtration and counter phishing by incorporating AI.
Marketing & Sales
Automation and AI fuels the e-commerce business model by enhancing retail experiences with the help of recommendation engines, sales predictions, and warehouse automation. Amazon, Alibaba, and eBay are large enterprises that have revolutionized the online retail market by adopting AI practices.
The relationship between marketing and sales is strengthened by intelligent recommendation systems. Apptus, an e-sales recommendation application, analyzes online search patterns and recommends products based on a predictive understanding of consumers' actions. The systems work by integrating machine learning algorithms and big data techniques.
Other examples of AI- based recommendation applications that score more online sales for their businesses include:
- Netflix and YouTube – Video suggestions in the entertainment industry
- Spotify and Last.fm – Song suggestions
- Bigbasket – Recommendations of grocery products
- Readgeek – Recommendations of books
AI in Health Care
Artificial Intelligence has empowered doctors and operational teams to improve their clinical efficiency and make timely informed decisions. Machine learning, data transparency, and reporting has supported efficient drug discovery, clinical forecasting, personalized engagement, and advanced clinical research, among many other breakthroughs.
Ubiquitous health trackers such as FitBit, Apple, and Garmin have provided an easy reporting system to elderly patients by eliminating the need for regular visits to hospitals.
Intelligent Robotic Agents in healthcare operations are evolving and improving their accuracy in disease detection; in fact, they can now perform complex surgeries with precision in developed countries. Automating healthcare operations secures the process of accessing patient records, which results in more efficient care and quick recoveries.
AI/ML-Enabled Crowdbotics Services
Crowdbotics, an up-to-the-mark service provider in the software industry, also integrates machine learning capabilities with development packages and libraries. The Crowdbotics App Builder supports real-time production and deployment by enabling high-quality custom add-ons to utility features.
For example, you can build an AI-powered ChatBot application for your business with Crowdbotics. Every application built with Crowdbotics is guaranteed to have efficient and high-quality development support. Crowdbotics will take care of your desired design, business logic, infrastructure, implementation, maintenance, operations, monitoring, and security.
Here's what the development roadmap looks like:
In general, Crowdbotics allows you to easily scale your application with your business infrastructure in a short time. Crowdbotics eliminates the need for error-prone manual code operations. It can integrate with your existing software release process or round-the-clock delivery tool-chain (e.g., GitHub, Slack etc). It also provides you a window to view product development at any phase in order to enable revisions and transparent cost analysis.
Crowdbotics is an easy-to-adopt, fully-functional, managed tool which gives you application code provision with entitlement and AI integrations. Build your next app with Crowdbotics and grow your business with a flourish!
In recent years, the upward trajectory of Artificial Intelligence has propelled the global business market to increased efficiency, security, and productivity. It is imperative to maintain the development of AI technology and develop state-of-the art AI-driven solutions across departments to set new benchmarks across all industries.