Confused About AI?
Find out more, by reading our Artificial Intelligence FAQs.
WHAT IS AI?
AI, or Artificial Intelligence, refers to the simulation of human intelligence processes by machines, enabling them to perform tasks that typically require human cognitive abilities. This can include learning, reasoning, problem-solving, perception, and language understanding. AI technologies, such as machine learning and deep learning, analyse data, identify patterns, and make decisions autonomously. Sendient uses AI to develop innovative solutions and services that help organisations automate processes, gain insights from data, and enhance decision-making capabilities.
HOW COULD AI HELP MY BUSINESS?
AI could benefit your business in numerous ways. It could automate repetitive tasks and enhance decision-making processes with data-driven insight. It could improve customer experiences through personalised interactions, and optimise operations for greater efficiency. Additionally, AI could enable predictive analytics to anticipate market trends and identify opportunities. Sendient offers bespoke AI services that are uniquely align with our clients business objectives. This helps them innovate and drive business efficiencies.
WHAT'S THE DIFFERENCE BETWEEN AI AND ML?
Artificial Intelligence (AI) is an umbrella phrase that is often used to describe solutions that can perform tasks that typically require human intelligence. Machine Learning (ML), is regarded as a subset of AI that involves teaching machines to learn from data without being explicitly programmed. Whilst AI encompasses a range of techniques aimed at replicating human-like intelligence, Machine Learning specifically refers to the ability of machines to learn and improve from experience without being explicitly programmed for every task.
WHAT IS A LARGE LANGUAGE MODEL?
A large language model (LLM) is a type of Artificial Intelligence model that has been trained on vast amounts of text data to understand and generate human-like language. These models, such as GPT-3, GPT-3.5 and GPT-4, are capable of performing a wide range of natural language processing tasks, including text generation, summarisation, translation, and more. Due to their extensive training data and complex architecture, LLMs exhibit remarkably strong capabilities in understanding and generating human readable text.
HOW CAN A BUSINESS USE A LLM?
Organisations can leverage Large Language Model (LLMs) like Chat-GPT to enhance many aspects of their business. This can include generating compelling marketing material and personalised customer communications to automating administrative tasks and improving decision-making processes. Large Language Models have the ability to analyse data and predict trends that can help make them more competitive. To unlock the true potential of models such as GPT-4, Sendient recommends that organisations will need to undertake some form of integration activity, interfacing with the likes of Microsoft Azure, and using either Power platform or Logic apps to really start to transform their businesses and drive efficiencies.
HOW CAN MY BUSINESS USE CHATGPT?
ChatGPT is a front end chatbot that uses GPT-3, GPT-3.5 and GPT-4 models. Organisations can very easily and cost effectively utilise ChatGPT to improve customer support by providing instant responses to inquiries, reducing response times, and improving customer satisfaction. Additionally, Chat-GPT can enhance internal communication, automate routine tasks, and assist with decision-making processes. With Chat-GPT, there is always a human in the loop, and in the free versions it is the older LLM models that are used. To unlock the true potential of models such as GPT-4, Sendient recommends that organisations will need to undertake some form of integration activity, interfacing with the likes of Microsoft Azure, and using either Power platform or Logic apps. This will allow them to really start to transform their businesses and drive efficiencies.
WHAT IS GENERATIVE AI?
Generative AI (Gen-AI) refers to Artificial Intelligence systems that have the capability to generate new content, including images, text, music, and video that is similar to human-created content. These systems, powered by algorithms such as Generative Adversarial Networks (GANs) or Large Language Models (LLMs), can produce original and realistic outputs based on patterns and examples from existing data. Examples of Generative AI include OpenAI’s ChatGPT, Google Gemini and Anthropic Claude, all of which excel and generating text based documents. Gen-AI platforms such as DALE, SORA and Stable Diffusion are able to generate highly realistic images and videos.
WHAT TYPE OF DATA DO I NEED FOR AI?
For businesses to make the most of Artificial Intelligence they will need to access both structured and unstructured data sets. Structured data includes organised information stored in databases. This includes information such as customer demographics and sales transactions, as well as financial information and machine telemetry data. Unstructured data, can include documents and reports, as well as online content including social media posts or images. Unstructured data lacks a predefined format but holds valuable insights that can be leveraged by LLMs extensively. By combining structured data with unstructured data, AI can provide comprehensive insights that can help your business drive increased efficiencies and growth.
HOW MUCH DATA DO I NEED FOR AI?
The amount of data needed for AI to have a positive impact on your business will vary from case to case. It will be impacted by the complexity of your operations and the specific AI applications you are considering implementing. Generally, having a diverse dataset comprising both structured (financial, sales data etc) and unstructured data (documents, reports, images and videos) is beneficial. By combining private data from internal sources with publicly available data from the Internet, Organisations can unlock valuable insights and build transformative AI programs.
HOW CAN AI DRIVE BUSINESS EFFICIENCY?
AI can drives business efficiency by automating repetitive tasks and streamlining processes. AI can provide data-driven insights that can help deliver informed decision-making. AI can enhances productivity, reduces errors, and optimise resource allocation. This can enable organisations to operate more efficiently, allocate resources effectively, and extend their operational reach.
HOW CAN AI HELP ME SELL MORE?
AI can help organisastions reach more customers by providing insights into customer preferences and behaviour. AI can facilitate targeted marketing campaigns and personalised product recommendations. It can automate sales processes, such as lead scoring and customer follow-ups, improving efficiency and increasing sales opportunities. In addition, AI powered analytics can identify trends and opportunities in the market, allowing you to adapt your forward facing sales strategies for maximum impact.
HOW CAN AI HELP ME REDUCE COSTS?
AI can help organisations reduce costs by automating repetitive tasks. It can optimise processes across departments, such as purchasing, finance, sales, marketing, engineering and customer service. This can lead to increased operational efficiency and lower overheads. AI-driven predictive analytics can be used to identify cost-saving opportunities, allowing you to make data-driven decisions that minimise expenses and improve profitability.
WHAT ARE THE DIFFERENT TYPES OF ARTIFICIAL INTELLIGENCE?
There are lots of ways to define AI, and categorise it based upon use case, function and form. However, Sendient typically categorises AI in to 3 separate forms.
Narrow AI, (also known as weak AI), is designed to perform specific tasks, such as speech recognition or image classification. It is very capable of the narrow task that it is built to undertake, however it is not able to do wider tasks. LLMS such as ChatGPT would typically be described as being Narrow AI..
General AI, (sometimes referred to as strong AI), has a much wider capability and can undertake many knowledge based tasks – similar to a human being. This might include knowledge and skill based activities and it might also include movement or motion. Many organisations are working General AI solutions, however at this point, these are still in the research phase with nothing that is widely operational.
Artificial General Intelligence (Sometimes referred to as superintelligent AI) is a hypothetical form of AI, that would surpasses human intelligence and capabilities in every aspect. There are no AGI solutions or services today. Industry commentators believe that we are still many years away from any form of AGI type capability.
Currently, narrow AI is the most prevalent form of AI, with applications in various industries, while general and superintelligent AI remain largely theoretical.
HOW DOES ARTIFICIAL INTELLIGENCE WORK?
Artificial Intelligence (AI) is a sub-component of computer science that aims to create intelligent platforms, programs and systems that are capable of performing tasks that typically require human intelligence. AI works by mimicking the cognitive functions of the human brain, such as learning, reasoning, problem-solving, and perception.
AI systems are built upon a series of mathematical algorithms, which define a sets of rules to process vast amounts of data and extract meaningful insight. These algorithms enable AI systems to identify patterns, make predictions, and adapt to new information.
Machine learning, a subset of AI, allows systems to learn from data without being explicitly programmed, by identifying patterns and making decisions based on past experiences. At its heart Machine learning makes extensive use of mathematics and statistics, which are used to generate insight and intelligence.
Deep learning is another frequently discussed subset of AI. Deep Learning involves training artificial neural networks with large datasets to perform specific tasks, such as image recognition, pattern matching or natural language processing. These neural networks consist of interconnected layers of artificial neurons, which consume inputs and generate outputs.
Overall, AI systems work by processing data, learning from it, and applying insights to perform tasks autonomously. By feeding AI systems with structured data and unstructured data, organisations can automate processes, generate new insights, and build significant efficiencies in to their structures.
HOW WILL ARTIFICIAL INTELLIGENCE IMPACT JOBS?
Artificial Intelligence could impact jobs by automating routine tasks and augmenting human capabilities in various industries. While AI may lead to the displacement of some roles, it will also create new job opportunities in AI development, data analysis, and human-AI collaboration. Labour forces rarely remain static, and as new services and consumer needs change, so the labour force has historically changed. A great example might be post covid, there has been a huge increase in the number of delivery drivers, package handling depots and logistics centres as consumer buying preferences have moved online. In the future it is possible that deliveries might be fulfilled by drones, and this in turn may result in some displacement of delivery driver roles. However, as the demand for drones grows, so their will be increased labour requirements in manufacturing facilities that focus on building energy efficient drones. AI may make impact some roles that exist today, however there are likely to be many new roles created as a consequence of this new and enabling technology.
WHAT ARE THE REAL-WORLD APPLICATIONS FOR ARTIFICIAL INTELLIGENCE?
There are huge numbers of practical applications for Artificial Intelligence within business. Please visit our Use-Case pages for examples of how AI is being used in business.
WHAT ARE THE ETHICAL CONSIDERATIONS FOR ARTIFICIAL INTELLIGENCE?
AI and Ethics is a huge topic, and there is considerable focus and efforts going into research within this space. Ethical considerations surrounding Artificial Intelligence (AI)
include concerns about bias in AI algorithms, privacy implications of data collection and usage, and the potential for job displacement due to increased automation. In addition, there are other ethical considerations around transparency and accountability in AI decision-making processes, as well as the impact of AI on societal norms and values. There isn’t a single answer or approach on how to deploy ethical AI, however it is important that organisations give the topic some consideration. As a minimum organisations should think about how they implement fair and transparent AI practices, ensuring responsible data usage, and prioritising the well-being of individuals.
WHAT IS AI COMPLIANCE?
In early 2024, there are no AI regulations that organisastions need to comply with explicitly, however there are many data handling and data protection regulations (such as GDPR and HIPAA) that define how data can and cannot be used. These regulations have an impact on how data could be used by AI, and organisations and individuals need to ensure that they manage any data shared with an AI model in accordance with the data regulations. Numerous governments and agencies around the world are discussing AI regulation, and it is conceivable that there will be new AI regulations launched in the years ahead.
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