What is Artificial Intelligence (AI)

Artificial intelligence (AI) is a part of computer science-related to building machines that can perform the task that requires human intelligence. It is the science of the simulation of human intelligence in machines that are programmed to think and imitate human-like actions. 

                                                                      Content Courtesy Investopedia

Categorization of Artificial Intelligence

Artificial intelligence may be divided into two categories: weak and strong. 

Weak artificial intelligence refers to a machine or system designed to carry out a single task. Weak AI includes games such as chess or card games we play online and personal assistants like Google’s Assistant, Amazon's Alexa, and Apple's Siri. Where you ask the assistant any question and you get relevant replies.

Strong artificial intelligence refers to a system that carries out human-like tasks. It is a more complicated and complex system programmed to handle situations with human intervention or minimal human touch. Examples like self-driving cars or robotic medical equipment used for operation-related procedures.

Building blocks for AI

Building blocks are important to designing and assembling AI structures. AI Vendors offer the primary capability that every block possesses, but companies often regulate blocks to create customized packages. The exhibit below organizes building blocks according to whether they pertain primarily to data, processing, or to action.

Infographic courtesy- BCG

Adoption of Artificial Intelligence and its impact

“As per a published report by McKinsey & Company, the finding of their global survey suggests that there is a 25% Year-on-Year increase in the use of AI in the standard business processes of organizations.”

The report also suggests that AI adoption is increasing nearly in all sectors. High Tech sectors are leading adopters of AI in their processes followed by Automotive & assembly, Finance Telecom, Travel transport & logistics. The retail sector is going aggressive every passing year.

As per reports, Retail has seen the largest increase, with 60 percent of companies embedding at least one AI capability in one or more functions or businesses.

The positive impact of AI

“Adoption of AI helps in revenue growth and report suggests the most positively affected function which sees the growth in revenue quite often is Marketing & Sales. While the adoption helps the considerable cost decrease in manufacturing function.”

As per an article/blog published, There are ten different sectors ranked from highest to lowest based on the percentage of firms adopting AI technology.

1. High tech and telecommunications (~31%)
2. Automotive and assembly (~29%)
3. Financial services (~27.5%)
4. Energy and resources (~27%)
5. Media and entertainment (~22.5%)
6. Transportation and logistics (~21%)
7. Consumer packaged goods (~20%)
8. Retail (~19%)
9. Education (~16.5%)
10. Health care (~16%)

The sectors of telecommunications and financial services have the highest potential to use AI in marketing, while health care and education have the lowest potential to invest in AI.

Functional Areas Where AI is being used in 2022

• Research & Development
• Customer Service
• IT
• Operations, Facilities, Fleet Management
• Marketing, Advertising & PR
• Finance & Accounting
• Manufacturing & Production
• Sales
• Purchasing, Logistics, Supply Chain
• Human Resources
• Distribution
• Legal
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Why AI is a necessity post-covid business environment

Some enterprises now have considerable experience with digital technologies including integration and simple data processing. But AI, which helps machines to solve problems and perform actions that only humans could do earlier, goes far deeper than that. AI technologies study huge data sets to understand the fundamental patterns, allowing computer systems to make complicated judgments, interpret human actions, and, among many other things, identify images and recognize the human voice. The AI-enabled systems often learn and adapt continuously. These AI capabilities of organizations are going to be a great help when they confront the post covid 19 crisis situations see the exhibit below

Artificial Intelligence (AI) in Marketing

AI in Marketing utilizes artificial intelligence technology to make automated decisions that enhance marketing strategies based on data collections, data interpretation, and additional consumer, economic, and other important patterns. AI is widely used in campaigns where the pace is an essential element of performance.

Artificial Intelligence tools use data and user profiles to learn how to create better connections with consumers and then send customized messages at the right time without any human intervention to ensure an optimum level of efficiency in marketing communications.

“AI is implemented to help marketing carrying out complex tasks with very little or no human complexity”

Key Elements of Artificial intelligence

• Machine Learning
• Big Data
• Smart & Powerful Solution

Machine Learning: 

When user preferences grow for more customized, appropriate, and supportive interactions, machine learning becomes an essential tool to fulfill those demands. It lets advertisers build better segmentation of consumers, produce more specific innovative strategies, and monitor performance efficiency. In fact, most executives have started believing that by using machine learning and AI tools they can achieve sustainable competitive advantage.

Machine learning is at its core is a method of easily marking and processing large data sets. It helps marketers to identify trends or common occurrences to predict common responses effectively to understand the root cause and likelihood of certain customer behavior. Marketers may achieve this on their own, but a computer is helping them do that with high speed. As per reports, most marketing leaders agree that automation and machine learning would enable their team to focus more on productive planning & strategic activities.

There are three key considerations every marketer should make to prepare their organization for machine learning: -

1. Define Your Goal to implement Machine Learning in Marketing
2. Machine Learning Algorithm with relevant & large number of data sets
3. A diverse team with the right mindset

Big Data 

Big data is the mixed set of structured, semi-structured, and unstructured data generated and collected by organizations used in machine learning applications for advanced analytics. It also refers to the capability of a marketer to work on vast data sets with a limited human touch.

After aggregating the data, marketing departments can use these data to ensure that the personalized message is sent to the right consumer at the right moment, through their medium of preference.

In the year 2001, Doug Laney, then an analyst at Meta Group Inc. characterized big data with 3Vs

Volume of data

Variety of data sets

The velocity of data generation, collection & storage

“The greater the volume of data, the stronger the trend and pattern analysis would be. There is a massive volume of data out there especially on social media waiting to be cleansed, structured, and analyzed using predictive analytics for predicting user’s buying patterns.”

The key marketing applications of big data  

Knowing the target users’ demography,

Being able to recognize the characteristics, interests, and habits of consumers

Helping companies to develop more effective advertising, communication & product strategies.

Providing marketers with a greater chance of sales conversion

Powerful Solution

• AI Marketing Tools with the help of big data understand the user environment and view sentiment and conversation much like a human which allows them to identify and understand the information gathered from interactive platforms like social media & email. These tools, by using large data sets identify insights much quicker & faster than humans.

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• Key Competitive Advantage of AI in Marketing

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• “Artificial intelligence helps revolutionizing multiple sectors and industries . If we just look at the marketing industry, marketers use AI tools to boost their user targeting, generate leads, provide user support efficiently, enhance the user interface and user experience on their web destinations”

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• Some of the key competitive advantages a marketer can derive from AI are: -

Driving operational costs down while growing the revenue

Creating consumer or user personalization and convenience.

Anticipating user needs and behaviors.

Deriving more and better actionable insights from business data.

Considerable reduction in time spent on repetitive, data-driven tasks.

Increasing their ROI on campaigns.

Transforming their traditional marketing function to an intelligent function

Establish a long-lasting relationship with the brand users.

Chatbot

Smart Automated Digital Campaigns

Personalized Website Designs

Search Engine Results

Voice Search tools like Alexa, Google Assistant

Automated Content Curation & Generation

Multi-Channel Marketing Attribution using Predictive Analytics

Personalized Emails

Dynamic Pricing in E-Commerce

AI-powered Image Recognition

AI-powered product & services recommendations

AI-Powered Social listening

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• Core Challenges in Artificial Intelligence implementation

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• Some of the significant challenges and barriers that organizations are facing to implement AI in their business processes are: -

Lack of Focussed Strategy for AI

Scarce of talent with appropriate skill sets

Lack of ownership and commitment from Organisation leaders

Lack of Tech-Infra Support to AI

Lack of Big Data generation and collection system in Organization

Uncertainty or risk in investment in AI

Lack of enough workforce to manage AI vertical

Limited usefulness and relevance of data and insights coming from AI

Personal decision-making overrides AI insights

No change in frontline processes post AI implementations

Lack of National and International policies, rights & regulations

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• How to overcome AI implementation challenges & Barriers

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Create case studies based on data and facts for the management or keyboard members to educate them with benefit-driven insights for quick AI implementation in business processes.

Understand the required skill-sets for AI implementation at various stages of your growth cycle.

Hire those in the team who possess those skillsets

Allocate AI-training budget for current team’s skill enhancements.

Create a robust data management process

You may be facing challenges to build an AI-driven business process but once successfully implemented it can deliver huge value to your business consistently year on year. 

Summary

You must start early with small AI projects, and get your key decision-makers and existing team aligned with the complete roadmap for implementation, you will have a very good chance of successful implementation of AI-driven marketing & other key business processes. And if there is a need to outsource some or all of the AI-driven business process implementation. You can trust Team BrandGyani’s AI development team to fulfill the gap that may be caused due to the lack of the right skill-based resources in-house.

(This Article/Blog has been curated by Gitanjali Mishra from our Research and Article Team)