49%
of organisations have deployed any AI projects in the past five years
Leveraging data platforms, data science and data engineering to drive real value.
Rethink your data strategyThe barriers to AI adoption are complex. Firstly, there is a lack of coherent strategy surrounding AI deployments, characterised by limited knowledge on where to implement AI and a lack of consideration about how to best accelerate AI projects.
Secondly, a significant number of organisations do not have a dedicated person or team driving AI adoption. This make it difficult to see the tangible results of AI projects, but it also leads to the third major barrier which is a lack of AI projects being deployed in organisations at all.
We commissioned a YouGov survey of over 1,000 senior decision makers, including owners, partners, chairpersons and non-executive directors, working across the public and private sectors. Adopting and integrating any new technology into an organisation is difficult. Not only does there need to be a sound business case for its introduction and a clear strategy for integration from the start; factors such as resource, talent and spend have to be taken into consideration at every stage of the rollout. This is especially true when it comes to AI.
Successfully integrating AI into a business environment requires a number of factors, but chiefly: highly skilled, experienced data scientists buy-in right from the bottom to the top of the entire company a clear strategy and tactics for implementation.
This however, only happens with a full understanding of AI and what it can do for the business.
The research shows there is a substantial lack of knowledge at the board level, with 29% revealing they have no idea where to apply AI to their business process. A further 26% said that they find the lack of internal knowledge around AI to be a key barrier to implementation across the organisation.
To overcome these barriers to adoption, a collaborative approach to AI is needed. With a rigorous process to define where AI will bring the most value to the business, and where to focus and prioritise project implementation, a clear, concise strategy will emerge. This highlights who needs to be in the driving seat to oversee the successful implementation and scaling of AI in the enterprise.
of organisations have deployed any AI projects in the past five years
of senior executives are unaware of the maturity level of AI or Machine Learning in their company
had fewer than 10 people dedicated to AI development in entire business
of organisations have a dedicated role for integrating emerging technologies such as AI and Machine Learning into their business
of the organisations that have deployed AI in the last two to five years have a clear view of the tangible benefits these projects have brought the business
of the executives cited the inability to find available talent in data science as a key barrier to implementing AI programmes within their organisation
Working closely with your business leaders we first understand your organisational goals, and then set out for you the enterprise data collection and exploitation strategies that will move the needle.
Our data strategists, data engineers and data science experts keep this process grounded in reality – offering expert advice through this process to identify quick wins and to avoid projects that are technically risky with little or no return.
"“Many organisations lack a clear business case as to why they should commit time and money to creating an AI strategy. There are clear benefits that AI offers enterprises, and these are well known. Companies need to take more seriously the opportunity that AI offers and include discussions at the board level to increase deployments to see tangible benefits.”"
Gary Richardson Chief Digital Officer, 6point6