Artificial intelligence is reshaping the global business landscape, disrupting the traditional rules and assumptions of business and transforming the way companies operate, compete and grow. Some early adopters of AI capabilities are already financially outperforming their industry peers – especially those that are using AI to improve operations, optimise customer experience and develop their business ecosystems.
Over the next three years, over 92% of companies plan to increase their investments in AI-based solutions, however, only 1% of business leaders feel that AI has been fully integrated into workflows to drive business outcomes. This is further exacerbated by an AI skills gap with, by some accounts, more than 70% of workers needing more training in this area.
But strategies to close skills gaps are falling short. As the demand for AI skills rapidly rises, organisations are left wondering whether they should focus their recruiting on employees equipped with AI skills, upskill their existing workforce or outsource to fill the gaps.
While outsourcing AI development and capabilities might seem like a fast and easy solution, building in-house AI capabilities brings incomparable, long-term strategic value.
In-house AI team benefits
A major concern for organisations adopting AI is compliance, whether that’s with external regulatory frameworks or internal business objectives and guidelines.
An internal AI team gives organisations more control over the design, development and deployment of AI, to make sure that any solutions can be closely aligned with the company’s goals, culture and pace.
This approach eliminates the friction of working with external providers that may not fully grasp business demands or operational context. Additionally, in developing and training AI-based systems, it is highly likely that the team will need to work with sensitive data or strategic insights, where control and oversight become critically important.
An in-house expert will be able to drive speed and agility, ensuring AI models iterate faster, respond more quickly to business needs and adapt based on frontline feedback. They can also prototype and refine deployments in real time, significantly reducing the turnaround time for testing and deployment.
Naturally, this is dependent on establishing a highly skilled in-house team and internal processes that are not limited by organisational bureaucracies.
One frequently overlooked benefit of building an in-house AI team is a better use of proprietary data for training and developing AI-based systems. In-house teams will simply be better equipped to handle proprietary business data securely. But they will also have deeper insight into deciphering what the data really represents and understanding how it can add value to the business.
The results will be reflected in the accuracy, reliability and relevance of the outputs from the AI models. In-house teams work with less friction and will be able to partner closely with other teams across the organisation to design and develop services that are grounded in business realities, leading to better adoption and more meaningful outcomes.
Internal teams can also help businesses differentiate themselves from those using off-the-shelf products, available to anyone. They can design and build custom AI products, better optimise operations and craft personalised customer experiences.
Working with external consultants and technology providers can be a clever way to jump-start AI applications – particularly for learning, exploring and accelerating early AI use cases or pilot projects – but should be considered a starting point.
External support could help upskill internal teams, test new ideas and build initial momentum, but to truly realise the strategic value of AI for business, organisations need robust in-house capabilities. Organisations that recognise this early and invest accordingly will be the ones that lead in the age of intelligent enterprises.
Kamales Lardi is an internationally-renowned thought leader in AI and digital transformation and the author of Artificial Intelligence for Business.
Artificial intelligence is reshaping the global business landscape, disrupting the traditional rules and assumptions of business and transforming the way companies operate, compete and grow. Some early adopters of AI capabilities are already financially outperforming their industry peers – especially those that are using AI to improve operations, optimise customer experience and develop their business ecosystems.
Over the next three years, over 92% of companies plan to increase their investments in AI-based solutions, however, only 1% of business leaders feel that AI has been fully integrated into workflows to drive business outcomes. This is further exacerbated by an AI skills gap with, by some accounts, more than 70% of workers needing more training in this area.
But strategies to close skills gaps are falling short. As the demand for AI skills rapidly rises, organisations are left wondering whether they should focus their recruiting on employees equipped with AI skills, upskill their existing workforce or outsource to fill the gaps.
