TALKING

Most industries want to integrate AI into their ways of working , with 55 % of organisations using AI in at least one business unit , up from 20 % in 2017 .

However , mastering the deployment of AI and doing so safely and ethically is paramount .

Not all AI copilots are created equal . It can be challenging to determine which copilot is best for your organisation ’ s team , whether they be part of your IT , sales or marketing departments . For example , Microsoft takes pride in positioning M365 Copilot as ‘ your copilot for work ’ due to its compliance with AI data standards and ability to integrate across all your day-to-day applications in the Microsoft ecosystem , such as Outlook , Teams , PowerPoint and Word . Consequently , your teams can access AI assistance consistently as they weave through a busy day of tasks .

Unlike ChatGPT , which uses AI and machine learning technology to generate text-written responses to questions , Copilot is present throughout your working day — assisting with organizational tasks , prompting and analysing data and providing integration into Office applications .

Your organisation should build a wish list based on AI business objectives and strategies . Relevant considerations include : What is your end goal ? Are there workplace inefficiencies that require correcting ?

Your organisation must also be certain they can achieve this adoption . To avoid delay or setbacks to deployment , your team needs to be able to demonstrate the value and impact of your adoption .

To do this , you ’ ll need a strategy that outlines a personalised set of outcomes , showing how this surplus of time and workforce will be better used . The benefits from this reallocation must not be lost or miscommunicated as the message ascends through management , so keep these straightforward . whole workforce ? Or might you look for a specific employee persona who can benefit the most ? A few prerequisites are also needed before your copilot can be fully integrated , including important administrative tasks such as assigning the appropriate base license . IT teams will need to make sure applications are updated across the entire team structure beforehand

to support integration and avoid the risk of slowing down the end-user experience .

Firstly , AI governance needs to be up to date – establishing safe and ethical AI systems within your organisation should be a top priority for your team .

Organisations should be wary of choosing the wrong ai for the wrong person .

Guardrails and legal frameworks must be followed to ensure that a high level of diligence is introduced and maintained when using this technology .

Those related to data security are also high on the list of risks to watch out for . AI-generated information is accessed through the sharing of data repositories . Within these repositories , leaders need to ensure that data is being properly managed to get the most accurate results . To put it bluntly , ‘ rubbish in , rubbish out ’ means if you are feeding your AI legacy or inaccurate data , it will use this to form the basis of its generated work and responses .

After deciding to invest , it is time to deploy your AI assistant to your users . First , who will get access ? Will it be rolled out indiscriminately to the

Highly versatile document management solutions like SharePoint , which have great value as a data repository , have become a ‘ dumping ground ’ for all

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