What Is Artificial Intelligence (AI)?

Artificial Intelligence (AI) seems to be everywhere and it’s already transforming how organisations across India operate. That’s because AI can help Indian businesses and their employees become more productive and efficient by helping with a variety of tasks, from automating processes to generating insights and driving innovation. As more companies adopt the technology in the country, it's also important to think about the ethical implications of AI and how to build trust in its capabilities. Let's take a closer look at what is AI, what it can do for Indian businesses, and how you can use it to achieve your goals.

What we’ll cover:

• What is artificial intelligence (AI)?
• What are the different types of AI — and what they can do for you
• What are the benefits of AI in business?
• What is AI’s benefit for industries?
• Trust in Artificial Intelligence
• Integrating AI with CRM
• Getting started with AI

Artificial Intelligence is the broad ability to have machines think and act like humans in processes like learning, reasoning, and problem-solving. Think of AI as a tool that can analyse data, make decisions, and perform tasks that would normally require human input. By analysing vast data sets, recognising patterns, and making predictions based on that data, AI allows machines to improve performance over time and generate new data and content.

AI systems are built with a range of capabilities that allow them to replicate human-like intelligence, including:

1. Machine Learning: This process entails the education of AI models to glean insights from data, recognise patterns and correlations, and forecast outcomes from fresh data.

2. Natural Language Processing: AI systems can be trained to understand, interpret, and generate human language, facilitating more natural interactions between humans and machines.

3. Computer Vision: One can educate AI systems to examine and comprehend visual information, such as pictures and videos, which allows it to identify faces and detect objects.

4. Decision-making: AI systems can be trained to make decisions by analysing data, weighing multiple factors, and selecting the most effective course of action.

5. Problem Solving: AI systems can be designed to find problems, develop solutions, and evaluate how well those solutions meet specific goals.

6. Generative AI: This type of AI focuses on creating new content based on existing data. In a CRM system, generative AI can be used to create a range of outputs, from writing personalised marketing content to generating synthetic data to test new features or strategies.

7. Predictive AI: Using data with AI and machine learning to find patterns, predict future events, and anticipate behaviours.

8. Autonomous AI: Systems that can operate independently without human intervention to make decisions and perform tasks by analysing data, learning from experiences, and adjusting to new inputs.

The terms "artificial intelligence" and "machine learning" are often used interchangeably, but the two have some key differences. Artificial intelligence refers to the ability to have machines think and act like humans in processes such as learning, reasoning, and problem-solving. Machine learning is a specialised field within AI. It allows computers to learn from data without being explicitly programmed. Machine learning algorithms empower computers to make decisions and predictions autonomously.

Simply, AI is a machine or a part of a machine that can do things usually associated with a human mind, like learning and problem-solving. Machine learning, on the other hand, specifically denotes learning through experience. AI often suggests a degree of human involvement in decision-making, while machine learning implies automated decision-making.

Officially, artificial intelligence was acknowledged in 1956, during the Dartmouth Conference, where researchers proposed that machines could simulate aspects of human learning and problem-solving. AI has since then evolved from theory into practical tools used by businesses around the world, including Salesforce.

AI works by analysing data, recognising patterns, and making informed decisions or predictions based on that data. In Salesforce, platforms like Agentforce use machine learning and natural language processing to automate tasks, and surface insights, thus helping teams achieve more with less resources and deliver more personalised customer experiences.

John McCarthy, a renowned computer scientist, is widely recognised as the “father of AI.” He not only coined the term “artificial intelligence” but also laid the groundwork for the ethical, intelligent systems, something that we’re building today at Salesforce.

Now, with the combination of massive amounts of accessible data, vast increases in computing power, and advances in deep learning algorithms, AI has the potential to largely transform how we live and work, and provide a massive boost to innovation and economic output.

To fully understand AI and its potential, it’s helpful to look at AI from two perspectives:

• Capabilities of AI: what AI can do for your business, and,
• Applications of AI: how AI does what it does.

AI systems can often be explained based on their capabilities- or how much intelligence they actually possess. The capabilities framework helps us understand how advanced AI is or could potentially become.

Narrow AI -

The most common type of AI today, it is designed to perform a single task, like classifying emails as spam or predicting the likelihood of a customer renewing their contract. For example, Salesforce’s Agentforce uses narrow AI to help service agents auto-classify cases, escalate urgent issues, and suggest knowledge articles in real-time.

• General AI -

It is still a futuristic concept, general AI woul dhave the reasoning power and flexibility of a human brain, and it will be able to learn and adapt across any domain.

Superintelligent AI-

This goes even further. AI that could outperform humans at virtually everything. Although not part of today’s business reality, the idea is indeed exciting.

In the real world, AI is more relatable when we look at how it helps solve problems. To understand what AI does today in practical terms, the “use case framework” is helpful. Here are a few key types of AI applications you’re probably already using — whether you know it or not:

Numeric predictions:

AI helps businesses make smarter, data-driven decisions. For example, it can help them forecast the next quarter’s revenue or optimise pricing.

Salesforce’s AI Cloud helps teams utilise pre-built models to predict churn, purchase probability, or case resolution times, all seamlessly integrated into Customer 360.

Classifications:

How do you know if a transaction is fraudulent or a customer service case is a high priority? Classification models help quickly categorise information to drive the desired action.

Salesforce’s Agentforce, for example, uses classification to tag cases, prioritise workloads, and match the right agent to the right case.

Robotic navigation

Think autonomous vehicles, or real-time logistics. Robotic navigation means AI can interpret and respond to the physical world.

When Salesforce’s Agentforce for Field Service uses AI to dynamically schedule field technicians based on location, availability, and job complexity, they ensure on-time service delivery and complete customer satisfaction, all powered by AI.

Natural Language Processing (NLP)

With an understanding of human language and the ability to generate conversations, AI can power intelligent assistants and chatbots with remarkable precision and human-like abilities.NLP helps analyse customer messages, summarise long case histories, and generate empathetic, brand-aligned replies, all in real time.

Generative AI

Generative AI is where creativity meets intelligence. Geneartive AI can create net-new content- text, images, code, and more.

Salesforce’s Agentforce offers suggested responses, summaries, and knowledge-based updates that are context-aware and consistent with your brand voice. Generative AI, when deployed this way, helps humans, not replaces them.

AI has the potential to transform businesses across various industries. For example, it can automate routine tasks, giving employees more time to focus on important work. AI-powered tools can even help with data entry, customer service requests, and inventory management so that employees can focus on more strategic tasks that grow the business. Here are some examples of where AI can help businesses:

AI can enhance the customer experience by providing personalised interactions and predicting what they’re likely to want next, based on what they’ve done in the past. Chatbots and virtual assistants powered by AI can offer real-time support and answer customer questions efficiently. AI-powered analytics can analyse customer data to gain insights into their preferences and behaviour, which helps businesses deliver personalised product recommendations, offers, and services.

AI enables businesses to make data-driven decisions by analysing large volumes of data and identifying patterns and trends that may not be immediately apparent to humans. This is done through grounding, which anchors AI systems in real-world data. AI-powered tools can process and analyze data from various sources, including social media, customer feedback, and sales records, to provide valuable insights and recommendations for improving business strategies.

By automating tasks, reducing manual labor, and optimising processes, AI can help businesses reduce costs and improve profitability. AI-powered systems can handle repetitive tasks with greater accuracy and efficiency. This saves employees time, offers customers faster service, and provides more personalised interactions, all of which improves customer retention to drive the business and boost revenue. AI can also optimise supply chain management, inventory control, and logistics, leading to cost savings and improved operational efficiency to achieve faster ROI.

One of the biggest ways that businesses can increase their productivity with AI is by working with AI agents, which act autonomously to help employees to get work done faster. By using an AI agent platform like Agentforce, employees across sales, service, marketing, commerce, and more, can focus on more complex tasks while agents manage more repetitive or mundane tasks.

AI can help sales teams streamline processes, enhance productivity, and drive sales growth. AI can automate repetitive tasks, analyse customer data to gain insights into customer behaviour, improve buying experiences, and boost sales. AI can also assist sales teams with predictive analytics, identifying potential leads, and optimising sales strategies.

AI has significantly transformed the customer service landscape by enabling businesses to provide faster, personalised support. AI-powered virtual assistants can handle customer queries, troubleshoot common issues, and offer relevant product recommendations. With AI, businesses can deliver 24/7 customer service, ensuring satisfaction and loyalty. Furthermore, AI can analyse customer feedback and sentiment to identify improvement areas and enhance overall service quality.

Read: 5 Ways AI Can Revolutionise CX in India

AI has also revolutionized marketing by enabling businesses to deliver targeted, personalised campaigns. By analysing customer data and predicting customer preferences, AI allows marketers to create tailored content and offers. AI-powered tools can automate email marketing, social media management, and ad targeting, optimising marketing efforts, and driving higher conversion rates. It can also provide valuable insights into marketing performance, helping businesses refine their strategies and achieve better results.

Read: The Indian CMO’s Guide to AI

Establishing trust in artificial intelligence (AI) is crucial for its successful and ethical implementation. You must have confidence in the reliability, accuracy, and security of AI systems to fully embrace their potential. Building trust in AI involves addressing several key concerns:

You know that the reliability and accuracy of AI systems are critical to building trust. That's why we advocate for rigorous testing, validation, and ongoing monitoring of AI algorithms. It also means implementing strong data management practices to safeguard the quality, relevance, and integrity of the data used to train and operate AI models.

It’s important that users understand how AI systems make decisions and why. When AI systems provide clear explanations for their decisions, users can be more confident that they’re making the right choices. This can be accomplished with user-friendly interfaces that explain how AI algorithms arrive at their conclusions, as well as documentation that provides more detail.

Security is a fundamental component of building trust in AI. By protecting user data and ensuring the privacy of personal information, businesses can build trust with their customers and stakeholders. Robust security measures must be implemented to safeguard data from unauthorised access, use, or disclosure. This involves employing encryption techniques, access controls, and regular security audits to mitigate potential vulnerabilities.

AI systems must be developed and deployed in an ethical manner, considering the potential impact on individuals and society. This involves addressing concerns such as bias, fairness, accountability, and potential job displacement. Ethical guidelines and principles should be established to ensure that AI systems are used for socially beneficial purposes and do not discriminate or cause harm.

AI systems are great at automating tasks and decision-making, but human oversight and control are essential to ensure responsible AI use that is aligned with human values and intentions. It's essential to have robust governance structures in place so AI systems remain subject to human review and intervention when needed.

Establishing trust in AI is a challenge that requires a comprehensive approach that addresses technical, communicative, ethical, and human-centred dimensions. By working to address all of these areas together, organisations can cultivate a climate of trust and confidence in AI systems. This will help pave the way for their broad implementation and use to realise their full potential.

Salesforce is promoting trusted AI with the Einstein Trust Layer. It is a secure AI architecture, built into the Salesforce platform. It is a set of agreements, security technology, and data and privacy controls used to keep your company safe while you explore generative AI solutions.

Learn more about Einstein Trust Layer with Trailhead

Customer Relationship Management (CRM) systems play a crucial role in managing customer interactions and data. Integrating AI with CRM can further enhance the capabilities of CRM systems and provide businesses with a 360-degree view of their customers.

Integrating the two can help you understand your customers better. They can analyse customer data and segment customers based on their preferences, behaviour, and demographics. This enables you to tailor your marketing and sales strategies to specific customer segments, resulting in more personalised and effective campaigns.

CRM and AI can help identify potential leads and qualify them based on their interactions with the business. This allows sales teams to focus on the most promising leads, improving lead conversion rates and sales efficiency.

Through the use of AI CRM, chatbots and AI agents are able to offer immediate assistance to customers, addressing their questions and resolving problems effectively. This leads to increased satisfaction among customers and alleviates the workload of human customer service agents.

AI can use customer data from CRM tools to give you complete context of your customers, helping you connect with them in a new way. It allows you to predict future trends and patterns by analysing historical data and customer behaviour, anticipating customer needs, and addressing potential issues before they become problems.

Implementing AI in your business may seem daunting, but there are several resources available to help you get started. Here are a few tips:

• Assess your needs and plan your approach: Identify the specific areas in your business where AI can add value. Consider tasks that are repetitive, data-intensive, or require human decision-making.
• Choose the right tools: Research and select the tools that best align with your business needs and technical expertise.
• Connect your customer data: A data platform lets you integrate large amounts of data from any source, standardise formats, and ensure consistency and integrity. You can’t expect all your data to live in one place, so you’ll need to create sharing mechanisms, such as data lakes or warehouses, to allow different departments to access and use the data.
• Invest in employee training: While about two-thirds of employees use or plan to use generative AI at work, nearly 61% of those who plan to incorporate the technology don’t know how to use trusted data sources or keep sensitive data secure. Educate your employees about AI and its potential impact on their roles. Provide training and support to ensure they are comfortable using AI tools and understand how AI can enhance their work. Trailhead is a free learning platform where you can upskill with today’s most in-demand skills. Here are a few trails to get you started:
  • Artificial Intelligence for Business
  • Prepare Your Data for AI
  • Responsible Creation of Artificial Intelligence

AI has the power to revolutionise the way businesses operate, providing significant benefits in terms of efficiency, customer experience, decision-making, innovation, and cost reduction. By integrating AI with CRM systems, businesses can further enhance their customer management capabilities and deliver personalised experiences. Embracing AI can unlock new opportunities for growth and success in the rapidly evolving business landscape.