Artificial Intelligence: A Roadmap for Sales and Marketing |...

Artificial Intelligence: A Roadmap for Sales and Marketing | Newsletter

2020/12/29 15:04In Software & Cloud Economics, Consulting Services, Thought Leadership

Artificial intelligence has been booming and showing no signs of slowing down. Our monthly newsletter covers all of the breaking stories in AI, along with future trends and new tools.

A Road Map For Artificial Intelligence In Sales And Marketing

Every company has got some automation - if not artificial intelligence (AI) - initiatives going on. Assess where you are with current projects and where you might want to go. Below is a list of critical use-cases on a road map to AI adoption, along with the complexity and advantages gained. Sales and marketing processes amenable to AI can be divided into these areas ordered from least to most complex:

Customer Support

• Chatbot
• Sentiment Analysis

Messaging

• One-to-one Content Marketing
• Dynamic Pricing

Conversion

• Sales Automation
• Market Prediction

Learn more here.

3 ways leaders fail their Artificial Intelligence (AI) projects

McKinsey's State of AI survey found that only 22 percent of companies using AI reported a sizable bottom-line impact. Why do so many projects fail, and how can leaders avoid this?

Most leaders pursuing AI miss out on three areas of ownership. These responsibilities start well before you plan your AI projects, and they extend long after your projects go live.

Let's break down three leadership traps and illustrate how successful artificial intelligence efforts avoided them.

Here are the three ways to fail your AI initiative: Mistake 1: Starting AI projects that don't align with the corporate vision Mistake 2: Waiting to plan for ROI after the project goes live Mistake 3: Expecting AI-driven transformation without fixing the organizational culture

Find out how to get AI past the innovation chasm in your organization here.

Artificial Intelligence 101 What is Image Annotation?

Image annotation is a key technique used to create training data for computer vision. In order for machines to perceive objects in their surroundings, annotated images are needed to train Machine Learning algorithms to learn to see the world as we do.

Annotation in Machine Learning is essentially the process of labelling data in the various mediums of images, text or video. The labels are usually predetermined by a machine learning engineer or computer vision scientist and are chosen to provide the computer vision model information on objects depicted in an image.

The algorithm would then use the annotated data to learn and recognize similar patterns when presented with fresh, new data.

Learn more.

The future of AI Five AI and ML trends for the workplace in 2021

Artificial intelligence (AI) and machine learning (ML) have been transforming our world for some time now, but the year 2020 has given these two game-changers new opportunity and urgency - with even greater developments anticipated in 2021.

Here is what to expect from AI and ML as the world continues to adapt in the year ahead:

AI will drive cloud innovation

AI-based applications and services are both driving cloud adoption, and benefiting from its popularity.

AI will focus on usability

In its earliest forms, AI wasn't about ease of use - it was about the algorithms. But today, many AI-enabled applications are increasingly focused on usability. In an ideal world, users won't have to know they're using AI at all - it will be seamless.

AI will benefit from the data explosion

The continuing proliferation of IoT devices, combined with faster microprocessors and the advent of 5G, will soon result in the continued exponential growth of data - and AI and ML developers will be making the most of it.

AI will instill more confidence

Artificial intelligence has come a long way in recent years in terms of acceptance and trust. As AI and ML use proliferate in 2021, that comfort level will increase.

AI will bolster predictive power

AI tools have evolved to draw conclusions and drive critical responses on a daily basis. Sophisticated data models enable officials to drill down to second-by-second information about regions, counties, and communities.

Learn more about the 5 AI trends for 2021.

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