Generative AI for business
In this guide:
- Artificial intelligence in business
- What is artificial intelligence (AI)?
- How are businesses using artificial intelligence?
- Business benefits of artificial intelligence
- Risks and limitations of artificial intelligence in business
- Examples of artificial intelligence use in business
- Generative AI for business
What is artificial intelligence (AI)?
Artificial intelligence refers to machines capable of intelligent behaviour - here's the definition, the difference between weak and strong AI, and how they are used in business
Artificial intelligence (AI) is a branch of computer science. AI technologies aim to reproduce or surpass abilities in computational systems that are generally deemed intelligent if performed by a human. These abilities include:
- learning
- reasoning
- pattern-recognition
- problem-solving
- visual perception
- language-understanding
Different types of artificial intelligence
There are two main types of artificial intelligence:
- Applied AI - is more common and includes systems designed to intelligently carry out a single task, eg move a driverless vehicle, or trade stocks and shares. This category is also known as 'weak' or 'narrow' AI.
- Generalised AI - is less common and includes systems or devices that can theoretically handle any task, as they carry enough intelligence to find solutions to unfamiliar problems. Generalised AI is also known as 'strong' AI. Examples of true strong AI don't currently exist, as these technologies are still in very early stages of development.
Many modern AI applications are enabled through a sub-field of AI known as 'machine learning'.
What is machine learning?
The roots of machine learning (ML) are in statistics. ML uses algorithms and statistical models to perform a specific task without using explicit instructions, instead relying on patterns and inference. For example, ML applications can:
- read a text and decide if the author is making a complaint or a purchase order
- listen to a piece of music and find other tunes to match the mood
- recognise images and classify them according to the elements they contain
- translate large volumes of text in real time
- accurately recognise faces, speech and objects
Generative AI leverages machine learning to interrogate vast amounts of data, and then generate original and realistic content based on the learned patterns. Find out more about generative AI for business.
How are AI and machine learning used in business?
Over the years, AI research has enabled many technological advances, including:
- virtual agents and chatbots
- suggestive web searches
- targeted advertising
- pattern recognition
- predictive analytics
- voice and speech recognition
- face recognition
- machine translation
- autonomous driving
- automatic scheduling
Many of these are now commonplace and provide solutions to a great number of business challenges and complex, real-world problems. For more AI use cases, see also how businesses are using artificial intelligence.
See also what is Industry 4.0 and discover examples of digital innovation in business.
ActionsAlso on this siteContent category
Source URL
/content/what-artificial-intelligence-ai
Links
How are businesses using artificial intelligence?
How to use artificial intelligence to improve your business performance, operational management, marketing and customer services, or simply seize new business opportunities
Artificial intelligence (AI) is steadily passing into everyday business use. From workflow management to trend predictions, AI has many different uses in business. It also provides new business opportunities.
Application of artificial intelligence in business
You can use AI technologies to:
- Improve customer services - eg use virtual assistant programs to provide real-time support to users (for example, with billing and other tasks).
- Automate workloads - eg collect and analyse data from smart sensors, or use machine learning (ML) algorithms to categorise work, automatically route service requests, etc.
- Generating new and original content - including images, text, music, code and even dynamically created video game elements.
- Optimise logistics - eg use AI-powered image recognition tools to monitor and optimise your infrastructure, plan transport routes, etc.
- Increase manufacturing output and efficiency - eg automate production line by integrating industrial robots into your workflow and teaching them to perform labour-intensive or mundane tasks.
- Prevent outages - eg use anomaly detection techniques to identify patterns that are likely to disrupt your business, such as an IT outage. Specific AI software may also help you to detect and deter security intrusions.
- Predict performance - eg use AI applications to determine when you might reach performance goals, such as response time to help desk calls.
- Predict behaviour - eg use ML algorithms to analyse patterns of online behaviour to, for example, serve tailored product offers, detect credit card fraud or target appropriate adverts.
- Manage and analyse your data - eg AI can help you interpret and mine your data more efficiently than ever before and provide meaningful insight into your assets, your brand, staff or customers.
- Improve your marketing and advertising - for example, effectively track user behaviour and automate many routine marketing tasks.
See further examples of artificial intelligence use in business, and read about potential uses of generative AI for business.
For more information on the different types of AI, see what is artificial intelligence or read about the business benefits of artificial intelligence.
ActionsAlso on this siteContent category
Source URL
/content/how-are-businesses-using-artificial-intelligence
Links
Business benefits of artificial intelligence
Find out about the advantages of artificial intelligence, including how AI can help you to reduce operational costs, increase efficiency, grow revenue and improve customer experience
Many businesses take up artificial intelligence (AI) technology to try to reduce operational costs, increase efficiency, grow revenue and improve customer experience.
For the greatest benefits, businesses should look at putting the full range of smart technologies - including machine learning, natural language processing, generative AI and more - into their processes and products. However, even businesses that are new to AI can reap major rewards.
Artificial intelligence impact on business
By deploying the right AI technology, your business may gain the ability to:
- save time and money by automating and optimising routine processes and tasks
- increase productivity and operational efficiencies
- make faster business decisions based on outputs from cognitive technologies
- avoid mistakes and 'human error', provided that AI systems are set up properly
- use insight to predict customer preferences and offer them a better, personalised experience
- mine vast amount of data to generate quality leads and grow your customer base
- increase revenue by identifying and maximising sales opportunities
- grow expertise by enabling analysis and offering intelligent advice and support
Commonly, one of the main reasons for using AI in business is competitive advantage. Other drivers include:
- an executive-led decision
- a particular business, operational or technical problem
- an internal experiment
- customer demand
- an unexpected solution to a problem
- an offshoot of another project
Benefits of AI and humans working together
Research suggests that AI doesn't always perform best on its own. AI technologies are great at driving or even replacing the lower-level, repetitive tasks, but businesses often achieve the greatest performance improvements when humans and machines work together.
To make the most of this powerful technology, you should consider AI as a means of augmenting rather than replacing human capabilities.
Read about other Industry 4.0 technologies and the business benefits of Industry 4.0.
AI opportunities for business
Whatever your reason for considering AI, the potential is there for it to change the way your business operates. All it takes to start is an open-minded attitude and a willingness to embrace new opportunities wherever and whenever possible.
Keep in mind, however, that AI is an emerging technology. As such, it is changing at a fast pace and may present some unexpected challenges. Read more about the risks and limitations of artificial intelligence in business.
ActionsAlso on this siteContent category
Source URL
/content/business-benefits-artificial-intelligence
Links
Risks and limitations of artificial intelligence in business
Find out about the risks of artificial intelligence for your business, and possible limitations of these new technologies
Businesses are increasingly looking for ways to put artificial intelligence (AI) technologies to work to improve their productivity, profitability and business results.
However, while there are many business benefits of artificial intelligence, there are also certain barriers and disadvantages to keep in mind.
Limitations of artificial intelligence
One of the main barriers to implementing AI is the availability of data. Data is often siloed or inconsistent and of poor quality, all of which presents challenges for businesses looking to create value from AI at scale. To overcome this, you should have a clear strategy from the outset for sourcing the data that your AI will require.
Another key roadblock to AI adoption is the skills shortage and the availability of technical staff with the experience and training necessary to effectively deploy and operate AI solutions. Research suggests experienced data scientists are in short supply as are other specialised data professionals skilled in machine learning, training good models, etc.
Cost is another key consideration with procuring AI technologies. Businesses that lack in-house skills or are unfamiliar with AI often have to outsource, which is where challenges of cost and maintenance come in. Due to their complex nature, smart technologies can be expensive and you can incur further costs for repair and ongoing maintenance. The computational cost for training data models etc can also be an additional expense.
Software programs need regular upgrading to adapt to the changing business environment and, in case of breakdown, present a risk of losing code or important data. Restoring this is often time-consuming and costly. However, this risk is no greater with AI than with other software development. Provided that the system is designed well and that those procuring AI understand their requirements and options, these risks can be mitigated.
See also Industry 4.0 challenges and risks.
Other AI limitations relate to:
- implementation times, which may be lengthy depending on what you are trying to implement
- integration challenges and lack of understanding of the state-of-the-art systems
- usability and interoperability with other systems and platforms
If you're deciding whether to take on AI-driven technology, you should also consider:
- customer privacy
- potential lack of transparency
- technological complexity
Find out more about the risks of generative AI in business.
AI and ethical concerns
With the rapid development of AI, a number of ethical issues have cropped up. These include:
- the potential of automation technology to give rise to job losses
- the need to redeploy or retrain employees to keep them in jobs
- fair distribution of wealth created by machines
- the effect of machine interaction on human behaviour and attention
- the need to address algorithmic bias originating from human bias in the data
- the security of AI systems (eg autonomous weapons) that can potentially cause damage
- the need to mitigate against unintended consequences, as smart machines are thought to learn and develop independently
While you can't ignore these risks, it is worth keeping in mind that advances in AI can - for the most part - create better business and better lives for everyone. If implemented responsibly, artificial intelligence has immense and beneficial potential.
Also on this siteContent category
Source URL
/content/risks-and-limitations-artificial-intelligence-business
Links
Examples of artificial intelligence use in business
Common applications of artificial intelligence technology in business, with examples of use in areas of business management, e-commerce and marketing
Artificial intelligence (AI) is all around us. You have likely used it on your daily commute, searching the web or checking your latest social media feed.
Whether you're aware of it or not, AI has a massive effect on your life, as well as your business. Here are some examples of AI that you may already be using daily.
Artificial intelligence in business management
Applications of AI in business management include:
- spam filters
- smart email categorisation
- voice to text features
- smart personal assistants, such as Siri, Cortana and Google Now
- automated responders and online customer support
- process automation
- sales and business forecasting
- security surveillance
- smart devices that adjust according to behaviour
- automated insights, especially for data-driven industries (eg financial services or e-commerce)
Artificial intelligence in e-commerce
AI in e-commerce can be evident in:
- smart searches and relevance features
- personalisation as a service
- product recommendations and purchase predictions
- fraud detection and prevention for online transactions
- dynamic price optimisation
Artificial intelligence in marketing
Examples of AI in marketing include:
- recommendations and content curation
- personalisation of news feeds
- pattern and image recognition
- language recognition - to digest unstructured data from customers and sales prospects
- ad targeting and optimised, real-time bidding
- customer segmentation
- social semantics and sentiment analysis
- automated web design
- predictive customer service
These are only some of the examples of AI uses in business. Generative AI has a whole raft of other potential applications and uses - see more on generative AI for business.
With the pace of development increasing, there will likely be much more to come in the near future. And with the emergence of new and diverse Industry 4.0 technologies, there are many other examples of digital innovation in business.
Find out more about the business benefits of artificial intelligence.
ActionsAlso on this siteContent category
Source URL
/content/examples-artificial-intelligence-use-business
Links
Generative AI for business
Understand the full potential of generative AI for business, and discover uses, applications, benefits and risk considerations.
In recent years, artificial intelligence (AI) has evolved into a powerful tool posed to transform the way businesses operate. At the forefront of this transformation is generative AI.
What is generative AI?
Generative AI is artificial intelligence capable of generating new and original content, including images, text, music, code and even dynamically created video game elements.
Rooted in machine learning, this subset of AI examines patterns such as style, structure and aesthetics from vast amounts of existing data. When prompted, it generates new material that is based on the features of the training data but contains new, original elements.
This ability to learn and replicate patterns from existing data is what makes generative AI a valuable tool promising to drive creativity, efficiency and competitiveness in business.
Potential uses and applications of generative AI
Generative AI has applications in a wide range of fields and business operations.
Content creation
Generative AI can create engaging, personalised and original content at scale. The most widely recognised tools in this field include ChatGPT, Bard and Copy.ai, although many more solutions exist. Examples of text generation outputs include news articles, social media posts, product descriptions, advertisements, code snippets, and even creative writing and poetry.
In addition to text generation, generative AI can create original artwork and offer new visual and auditory experiences through generated digital images, paintings, music compositions and more. Some more commonly known art generator tools include DALL-E, Craiyon and ArtBreeder. Examples of AI music generators include Aiva, Soundful and Riffusion.
Gaming
Video game developers are using generative AI to drive greater personalisation of gameplay. The technology allows players to contribute to the creation process and generate their game levels, characters, and realistic narratives, leading to a more immersive gaming experience. Examples of accessible generative AI tools for this include Unity ML-Agents, Houdini and Charisma AI.
Product or service personalisation
Generative AI can tailor experiences for individual customers. For example, push product recommendations in e-commerce and offer personalised messages or user interfaces that resonate with each customer's preferences. Examples of such tools include Adcreative.ai, Maverick, Lumalabs.ai and many others.
Innovation and product design
Businesses can leverage generative AI to facilitate design processes, create prototypes and simulations, and quickly generate and test product concepts. Some tools used for this include Stable Diffusion, Midjourney and Vizcom. By analysing market trends and preferences, AI technology can suggest features and designs that align with demand, leading to products that are more likely to succeed in the market.
Data augmentation
Businesses can use generative AI tools, such as Augmentor and DataRobot, to synthesise new data points similar to the original data, to improve the accuracy of data-based decision making in business. Practical applications include object detection, text classification, sentiment analysis, anomaly detection and more.
Benefits of using generative AI in business
From content generation to data augmentation, AI has the potential to improve efficiency across your business. Integration can also lead to:
- cost savings - through automation of a wide range of tasks
- faster innovation - leading to a shorter time to market and improved revenue streams
- increased productivity - including streamlining of creative processes and operations
- enhanced customer engagement - leading to improved brand loyalty and growth
- better data-driven insights - improving decision-making across the business
Generative AI can also offer businesses a substantial competitive advantage, especially for early adopters leveraging technology to position themselves at the forefront of their industries.
Concerns around generative AI in business
As with any novel technology, generative AI can pose certain business risks. You should consider them carefully to ensure responsible implementation and usage.
Reliability and authenticity
AI tools frequently interrogate data from unknown sources to create text and images. This data could be unverified, used without consent, or originate from an inadequately governed source. As a result, the media generated by AI could be unreliable, misleading or deceptive. It could also lead to reputational and financial risks should the images or text be based on someone else's intellectual property.
Ethical issues
As generative AI learns from existing data and creates content based on human text prompts, there is a potential for significant bias. If not addressed, this bias could intentionally or unintentionally result in the technology generating unfair or discriminatory content.
Quality control
There is no guarantee that the output generated through AI will meet the desired quality standard of your business. How well the system works for you largely depends on the source of data it uses. For example, an AI tool mining the internet for data using poor quality or irrelevant information may not generate an output aligning with your business values and brand identity.
Job displacement
The future of work is changing and the potential for generative AI to automate tasks may raise worries about job displacement. If you're considering integrating generative AI into your systems, you could think about using the technology not solely to automate tasks, but to empower employees to do more than they could before, and make them more productive. Alternatively, you could realign personnel toward tasks requiring critical thinking and empathy. This approach will not only minimise the negative impacts, but it can also help prepare your business for future growth.
Privacy and data security
Generative AI relies on vast datasets, including people's personal information. This method raises significant privacy concerns. Businesses must take steps to safeguard sensitive information and ensure compliance with data protection regulations before rushing to adopt novel AI.
To help with this, the Information Commissioner's Office (ICO) has set out eight questions for businesses that are developing or using generative AI that processes personal data. Their guidance on AI and data protection and accompanying risk toolkit further offer a roadmap to data protection compliance for developers and users of such technologies.
Applications of generative AI are diverse and promising, but require stringent safeguards to ensure that innovation and ingenuity in your business are driven safely and responsibly.
Also on this siteContent category
Source URL
/content/generative-ai-business
Links