What Is AI Software?

AI software mimics human thinking, learning and decision-making by processing large amounts of data, identifying patterns and making predictions or autonomous decisions. AI solutions range from simple automation tools to advanced machine learning systems that evolve through experience and interactions.

Businesses use AI software, such as virtual assistants, chatbots and generative AI, to automate tasks, enhance customer interactions and support employees. AI can streamline operations by automating repetitive tasks, improving decision-making, cutting costs and delivering more personalised customer experiences.

Most businesses have finance, marketing and HR departments that can benefit from AI. Financial teams can use AI for bookkeeping, invoicing and expense management. In marketing, AI can generate first drafts of ad copy and visuals for social media. HR professionals can automate contract renewals, vendor emails and employee onboarding.

Each business has unique needs, but certain features are essential for maximising AI’s potential. These capabilities allow AI software to analyse text, images, speech and numerical data, making it adaptable for various uses.

When evaluating AI software, look for the following key features:

• Intelligent Agent Automation and Development: Look for systems that enable the creation of highly specialised, task-specific AI agents. The software should support both low-code and pro-code development options to manage the entire lifecycle of these agents, automating a wide range of business processes to boost efficiency and productivity.
• Unified Data Processing and Activation: AI software can utilise and transform trusted data from any source into actionable insights. It should have the capability to bring together, understand and act on diverse data, ensuring that information is leveraged effectively across operations for smarter decision-making.
• Integrated Customer and Service Engagement: The platform should facilitate a seamless combination of human and AI capabilities to enhance customer interactions and reduce service costs. This includes support for comprehensive customer service management, field service, self-service portals, omnichannel engagement and robust contact centre operations, including voice and phone support.
• Enterprise-Grade Scalability and Ecosystem Integration: The software must be designed to scale with business growth, effectively handling increasing workloads and user demands. It should offer secure and open interoperability, allowing smooth integration with existing and new tools, resources and platforms to streamline operations and enhance team performance.
• Robust Data Security and Privacy Controls: Prioritise AI solutions with strong data security and privacy measures. The software should protect against data breaches and unauthorised access, particularly important for regulated industries and ensure compliance with privacy standards.
• Actionable Analytics and Performance Optimisation: The system should provide a command centre or similar capability to analyse and optimise AI performance from a unified view. It must be able to transform trusted data into actionable insights, empowering users to monitor key metrics, identify trends and make informed strategic decisions to continuously improve operations.

Businesses use AI to create ad content for social media marketing, generate images for the business’s website and provide customer support through AI agents. As AI adoption grows, organisations across all industries are seeing increased efficiency, cost savings and improved decision-making.

AI helps businesses optimise inventory management, reduce waste and improve operational efficiency. By leveraging real-time inventory data and predictive analytics, retailers can determine how much stock to order and when. Automating these processes saves money and avoids wasted labour.

AI in healthcare is revolutionising the industry for payers, providers and patients. AI-powered automation helps healthcare providers spend more time on patient care by handling provider network management, patient services and benefits verification. These help providers enhance patient care and offer a more accurate and speedy diagnosis.

Financial services institutions are subject to strict compliance and regulatory requirements. AI in banking and AI in financial services offer built-in solutions to help meet those standards. Today, many banks use AI for loan analysis, risk assessment and fraud detection. In financial services, wealth management and insurance, AI can help handle transaction disputes, processing insurance claims and managing complaints.

Agentic AI enables virtual agents to operate autonomously, making decisions and completing tasks without human oversight. By leveraging data and artificial intelligence, agentic AI increases employee productivity and unlocks new revenue opportunities. Agentic AI relies on self-contained agents — AI models designed with specific goals and abilities. AI agents are software applications powered by artificial intelligence that understand natural language, process commands and perform specific tasks to assist users. By analysing large datasets, AI agents refine their language understanding and anticipate user needs, allowing them to continuously learn and improve accuracy with each interaction.

AI agents are highly adaptable and capable of performing tasks without human oversight or direction. These autonomous agents learn from interactions, refine their decision-making and adjust their responses over time. Unlike traditional software programs, they can handle complex tasks using machine learning, natural language processing and real-time data analytics.

Agents are goal oriented and designed to achieve specific tasks. They evaluate specific tasks and determine the best way to accomplish them. Agentic systems are equipped with tools and services that help AI agents learn, adapt and collaborate to complete these tasks.

These systems rely on complex reasoning engines that mimic human-like decision-making using data, logic and preset rules.

Agentic AI enhances workplace efficiency by creating more personalised and engaging user interactions. These agents support employees by mimicking human decision-making and leveraging past interaction data to improve responses.

For example, AI in customer service helps human agents balance speed and quality. When a customer initiates a conversation with an AI agent, the technology pulls key details such as the customer’s personal information, account type, preferred language and past interactions. AI agents can handle simple tasks like scheduling appointments, sending help articles or answering common questions like business hours.

When the situation is too complex or requires human intervention, the AI agent passes the case to a human agent.

The best AI software varies depending on a business’s needs and goals. To choose the right solution, teams must identify potential vendors and evaluate how their AI software aligns with business objectives.

For most organisations, existing software or hardware is already in place. If so, it’s important to document legacy systems to determine whether the new AI software can integrate with current business systems and data.

Beyond large-scale organisational goals, different departments have unique requirements. Identify which teams will use the AI software and how they will benefit from it. Many types of AI software make it easier for cross-functional teams to collaborate and streamline existing workflows, making it essential to assess how different departments can best leverage AI capabilities.

When evaluating AI software vendors, enquire about the precautions and safeguards in place to ensure their AI is reliable and capable of protecting data. Speak with a representative to understand the available options regarding scalability.

Many businesses have already begun experimenting with AI software. Adoption is smoother when the new solution integrates with existing technologies. Some AI platforms, like Agentforce, include built-in integration with Salesforce business data and processes. Choosing AI software that complements existing tools rather than replacing them can help to reduce costs and avoid penalties for breaking ongoing contracts.