59% agree that competitive advantage depends on who has the most advanced generative AI.

72% of CEOs see industry disruption as a risk rather than an opportunity.

62% of CEOs say they will need to rewrite their business playbook to win in the future, rather than play to existing strengths.

Source: 2024 IBM Institute for Business Value

WHAT IS AI?

Artificial Intelligence, or AI, is a set of technologies that enable computers and machines to perform tasks that typically require human intelligence. This includes things like understanding language, recognising patterns, learning from data, and making decisions.

AI is a machine carrying out action and improving the action from experience to achieve its objective. Having processed our data, the answers these machines give are constrained by the narrow objectives for which they were designed.

Leaders must responsibly consider what AI is used for and what level is required for each application of AI given machines cannot sense or judge as part of their decision making.  Different levels of AI can be Active (human always makes final decision), Operational (AI performs decision making for micro tasks) or Systemic (micro and macro decisions made by AI) with changes being made by humans for intervention and training the AI.

What is Gen AI?

Generative artificial intelligence (AI) is a type of AI that can be used to create new content, including audio, code, images, text, simulations, and videos. Generative AI relies on sophisticated machine learning models. The large language models have been trained on trillions of parameters using that information to understand users natural language questions and respond with relevant new content.

<a href="https://storyset.com/online">Online illustrations by Storyset</a>

“Organisations have bought into the hype jumping to implement the latest Co Pilots. The digital assistants only save around 14 minutes per day for your workforce on tasks like finding information, writing documents and taking meeting minutes.

Taking meeting minutes for a meeting that didn’t need to occur with multiple employees in attendance is not enhancing your enterprise wide operating efficiency or revenue. 

We must approach AI linked to your strategy, considering end to end workflows and leveraging your data securely in your data platform. A focus on value identification, ability to scale and robust AI governance defined upfront is critical” 

Lindsey Hershman

Managing Director AI Access

What can you use AI for?

CONTENT CREATION

Generative AI can produce high-quality written content, graphics, and videos, significantly reducing the time and cost associated with marketing and communications. For example, AI can draft reports, generate social media posts, or create compelling ad copy, ensuring consistency and adherence to brand guidelines.

Product Development

By analysing vast datasets, generative AI can suggest new product designs, features, or improvements, fostering innovation. It can simulate and test these designs virtually, accelerating the development cycle and reducing R&D costs.

Customer Service

Advanced chatbots and virtual assistants powered by generative AI can provide personalised and efficient customer support. They can handle a wide range of inquiries, learn from interactions to improve responses, and ensure 24/7 availability.

Data Analysis and Insights

Generative AI can synthesise complex data into meaningful insights and predictive models. It can identify trends, forecast demand, optimise pricing strategies, and provide actionable business intelligence, enabling more informed decision-making.

Automation of Routine Tasks

Routine administrative tasks such as scheduling, data entry, and report generation can be automated using generative AI. This not only enhances efficiency but also allows employees to focus on more strategic and creative tasks.

Personalised Marketing

Generative AI can analyse customer data to create highly personalised marketing campaigns. By understanding customer preferences and behaviours, it can tailor content and offers to individual customers, improving engagement and conversion rates.

Strategic Advantages of AI

  1. Cost Efficiency: By automating content creation and routine tasks, generative AI can significantly reduce operational costs.

  2. Speed and Scalability: AI can process and generate outputs much faster than human capabilities, allowing businesses to scale operations quickly and respond to market changes in real-time.

  3. Innovation: The ability to generate new ideas and solutions can drive innovation, giving businesses a competitive edge in developing unique products and services.

  4. Enhanced Customer Experience: Personalised and efficient interactions foster customer satisfaction and loyalty.

54% of leaders expect AI to deliver cost savings in 2024. Of those, roughly half anticipate cost savings in excess of 10%, primarily through productivity gains in operations, customer service, and IT.

Source: 2024 BCG survey of 1,400+ C Suite Executives

Critical Risks to consider with Gen AI

  • Quality and Accuracy

    Generative AI can sometimes produce content that is inaccurate or of lower quality. For example, an AI- Generated report might contain factual errors or poorly written text, which could mislead stakeholders or damage the company’s reputation.

  • Intellectual Property Issues

    Since generative AI learns from existing data, there’s a risk of inadvertently copying proprietary or copyrighted material. This can lead to legal challenges and potential financial liabilities if the AI uses protected content without proper authorisation.

  • Bias and Fairness

    AI systems can inherit biases present in their training data, leading to outputs that might be discriminatory or unfair. This is particularly problematic in applications like hiring, customer service, or financial services, where biased decisions can harm the company’s reputation and result in regulatory scrutiny.

  • Security and Privacy

    Generative AI systems can be vulnerable to cyber attacks, where malicious actors could manipulate the AI to produce harmful content or access sensitive data. Ensuring robust security measures and compliance with privacy regulations is crucial to mitigating these risks.

  • Over-reliance and Skill Degradation

    Over-reliance on generative AI can lead to skill degradation among employees, as they may become too dependent on AI for tasks that require critical thinking and creativity. This could result in a workforce that is less capable of handling situations where human judgment is essential.

  • Ethical Concerns

    The use of generative AI raises various ethical questions, such as the transparency of AI-generated content and the potential for misuse in creating deceptive or harmful materials. Companies must navigate these ethical challenges carefully to maintain trust with customers and stakeholders.

  • Cost and Implementation

    While generative AI can drive efficiencies, the initial investment and ongoing maintenance costs can be significant. Additionally, implementing and integrating AI solutions into existing workflows can be complex and resource-intensive, requiring careful planning and management.

Want to know more? Get in touch today to see how AI can work for you.