Arguably the biggest thing to happen in artificial intelligence (AI) this year has been the hype surrounding generative AI (GenAI) models such as ChatGPT. This has pushed AI to the forefront of business conversations and the tech sector has been quick to capitalise on the opportunity. Hardware providers and software firms have all been busy building AI capabilities into their product families.
On the hardware side, this has meant more focus on AI acceleration hardware, where graphics processing units are added to servers to power machine learning and AI inference workloads. Such capabilities are needed for those organisations who want to run AI software in private clouds or on-premise rather than use the GPUs available as infrastructure as a service (IaaS) in the public cloud.
From an IT strategy perspective, among the first areas CIOs have been urged to look at is how AI can be deployed to automate and make IT operations more efficient.
According to analyst Gartner, generative AI will enable the democratisation of knowledge and skills by enabling the use of conversation and natural language. A Gartner poll of 1,400 executive leaders in September 2023 found that 55% of organisations are in piloting or production mode with GenAI. Jeffrey Hewitt, vice-president analyst at Gartner, said: “Generative AI products are democratising due to the confluence of cloud and open source.”
Tools such as ChatGPT have also been shown to produce and check code. Use of generative AI in software development and IT operations is likely to accelerate in 2024 as IT departments battle to keep on top of the backlog of work they are being asked to do.
“Democratised generative AI offers a new working paradigm and can present agility, adaptability and composability improvements for IT and operations,” said Hewitt. “If it is overused or used unnecessarily, it can generate unacceptable costs and negative environmental impacts.”
Beyond its use in IT processes, AI is being embedded in business software.
Microsoft’s roll-out of AI-powered Copilots for office productivity has given businesses a chance to start using AI to improve productivity. In Microsoft Teams, for instance, the AI is able to summarise meetings and suggest action points. In Excel, Microsoft has used AI to try to make it easier for people to analyse data. PowerPoint’s Copilot aims to speed up creating draft presentations and summaries. Similarly, in Word, the AI can be used to draft documents.
Microsoft is not alone. Google’s rival office productivity suite, Google Workspace, has also incorporated generative AI features. SAP is incorporating generative AI capabilities into software development and the Hana database, while Oracle has recently added AI capabilities for data management and business intelligence, and Salesforce has introduced its AI copilot Einstein 1.
Other enterprise software providers are busy adding generative AI capabilities to business software. This is likely to pan out in 2024, as AI enhanced business software is increasingly used as an approach to improve efficiency and productivity.
Here are Computer Weekly’s top 10 artificial intelligence stories of 2023.
1. Conversational AI vs. generative AI: What’s the difference?
As AI continues to evolve, understanding the differences and collaborative potential of conversational AI and generative AI is vital to their role in shaping the digital landscape.
2. Gartner Symposium: More about AI
The keynote presentation on the second day of the Gartner Symposium in Barcelona examined whether artificial intelligence should be more intelligent than humans. Guest keynote speaker Erik Brynjolfsson, senior fellow at Stanford Institute for human-centred artificial intelligence, predicted that next year, businesses will shift from experimenting with AI to implementing AI projects that start delivering business value.
3. The AI developer opportunity
Research has shown that AI has the potential to plug the skills gap in software development. Providers of robotic process automation (RPA) tools also see a huge opportunity in the use of AI-based code generation for speeding up RPA.
4. Chip sector gears up for AI revolution
Recognising the change in buying strategy among the hyperscalers and in anticipation of a shift to artificial intelligence (AI) workload optimisation among enterprise customers, semiconductor manufacturers are beginning to ramp up their AI portfolios.
5. Where is our National AI strategy heading?
The recent House of Lords Communications Committee expert witness session revealed a somewhat bizarre situation in government relating to our National AI strategy.
6. How generative AI and cloud complement each other
McKinsey partner explains the symbiotic relationship between generative AI and cloud, enabling organisations to speed up cloud migration and harness the benefits of AI.
7. SAP lays out generative AI strategy
SAP is incorporating generative AI capabilities into software development and the Hana database, prioritising data privacy and use cases that drive efficiency and cost savings for customers.
8. IT not ready for AI, Pure Storage survey finds
Storage, compute and networking hardware won’t cope without upgrades, and that often means total IT infrastructure overhaul.
9. Microsoft ignites chip journey with AI accelerators
The company used its annual Ignite conference to showcase the work it is doing to optimise AI and make more energy-efficient hardware.
10. Few organisations have a clear strategy for AI
Few organisations are confident with the main concepts involved in developing AI-enabled business models.
