Why organizations must address the AI skills gap [Q&A]

Skills gap

As AI sees wider adoption, the demand for skills surrounding the technology inevitably increases too. By failing to act to address this AI skills and leadership vacuum organizations could be taking a significant risk.

We spoke to Arun 'Rak' Ramchandran, president and global head -- GenAI consulting and practice, hi-tech and professional services at Hexaware, to find out more about the problem and how it can be tackled.

BN: What is the biggest challenge facing businesses as they look to experiment with AI adoption?

AR: Organisations are facing many issues when it comes to AI adoption, including security concerns, regulatory non-compliance, data bias, and hallucinations. These challenges not only limit the potential benefits of AI but also raise the possibility of financial or reputational damage. There are also challenges related to well-defined business metrics and Return On Investment (ROI), the readiness of enterprise data to be monetized, and handling change management in terms of workflows and organizational roles.

But arguably the biggest issue for many businesses, and linked to all the above, is the lack of AI skills and a leadership vacuum. This shortage is a real concern, considering recent studies show that one in six UK organizations have already deployed AI. With so much deployment underway, there is a real risk that without the right expertise or oversight, organizations could make costly mistakes and bloated investments.

Too often, businesses are finding they do not have the required skills, expertise, and accountability to fully benefit from AI. As a result, many AI deployments are not delivering as expected, with models generating outputs that cannot be put to use and flawed decision-making. Enterprises are then unable to spot these issues as they lack the expertise to understand what could be going wrong. In a nutshell, organizations are jumping on the AI bandwagon without fully thinking through all the practicalities of what AI entails.

BN: How widespread is the AI skills and leadership vacuum?

AR: This vacuum presents a widespread challenge affecting many organizations. Whether they are in finance or manufacturing, it does not matter. Businesses across different industries are finding it difficult to obtain the right skills to benefit from this technology.

LinkedIn's Future of Work Report reveals the extent of this problem -- as it reports a 21-fold increase in the amount of AI-related vacancies between November 2022 and August 2023. Whilst demand for AI talent will inevitability increase in line with deployments, it appears that many organizations are finding it hard to fill these roles. AWS found that almost three-quarters of UK businesses are struggling to find the AI talent they need.

Enterprises are also struggling to get the right leadership in place. This is causing a major headache as AI investments are being ramped up without someone in place to oversee them. One report finds that just over one in ten firms have appointed a chief AI officer, signaling a significant shortfall in AI leadership. Even if businesses can recruit technical AI skills by offering compelling salaries, these investments could be frittered away without the correct direction or leadership in place.

BN: So, what risks does this vacuum create for organisations?

AR: Since AI is still in an experimental stage, it is important businesses realize they could land themselves in trouble without the required skills or leadership in place. These elements will make it possible to have a clear game plan spelling out how AI can add value in the long term.

Additionally, there are challenges with setting clear business goals and ROI for AI projects, readying data for monetization, and adjusting workflows and organizational roles.

Worse still is the potential for regulatory non-compliance, IP leakage, or lasting reputational damage. This could be the result of employees tuning the model incorrectly or unintentionally letting biases creep into data. There could also be serious repercussions if staff fail to adjust for objectionable or non-compliant outputs or inadvertently mishandle sensitive data due to a lack of proper AI guardrails, governance, and oversight.

With so much at stake, organizations must not progress with AI deployments unless they have a clear view of what could go wrong. This approach risks leaving companies blind and vulnerable to the point of no return -- where damage is spotted far too late before anything can be rectified. The sooner enterprises get the right leadership and skills in place, the better as they can start to have a watertight plan that addresses every aspect of AI. This is critical given the continuing emergence of new AI regulations, such as the EU AI Act.

BN: What steps can businesses take to address this gap?

AR: To address the skill and leadership gap created by the rapid integration of Generative AI (Gen AI), businesses can take several steps. First, it is crucial to identify and cultivate AI leaders who blend deep technical understanding with strong governance and interpersonal skills. Such leaders should not only be proficient in AI technologies, but also adept in managing change and guiding teams.

Training existing leaders can be a highly effective strategy. Many organizations might benefit from upskilling an existing executive who already understands the company’s culture and business strategy. This approach uses their existing organizational knowledge while filling gaps in their AI expertise. It is essential, however, that these leaders receive comprehensive training in AI-specific skills, such as prompt engineering and system maintenance, to ensure they can manage the technical demands of AI projects.

Also, according to the Alan Turing Institute, successful AI leadership requires the capability to bridge the gap between technical and business units, facilitating communication and collaboration. This helps integrate AI solutions in a way that supports business objectives and minimizes disruption to existing processes.

Finally, to capitalize on the transformative potential of Gen AI, businesses should proactively create roles that cater to emerging needs -- like prompt engineers, large language model ops, visual designers, and content creators. These roles not only accommodate the new technology but also inject vitality into the tech sector, ensuring that the workforce evolves in tandem with technological advancements. By taking these steps, companies can mitigate the impact of the skills gap and align Gen AI deployments with long-term business goals.

BN: Do you have any other advice leaders should bear in mind to capitalise on the power of AI?

AR: 2023 was the year the world began to understand the true capabilities of Gen AI. It is safe to say that most organizations, including the creators, do not fully comprehend its future potential, or likely risks. It is also a good assumption that there will be an increase in the capabilities of Gen AI over time. Gen AI, coupled with traditional AI, is already proliferating with industry use cases that offer real quantifiable value and will open myriad opportunities. These opportunities will center around companies becoming more productive, enhancing growth, and creating new disruptive business models.

With most organizations already moving forward with AI, the time to act is now. The stakes are too high to engage in AI without proper leadership, talent, and a clear strategic vision. If they do not have all of the pieces of the puzzle to hand, organizations should draw on the technical expertise of an external services partner well-versed in AI technologies. The benefit of doing this is twofold. Not only could companies supplement the soft skills of their transitioned leaders with the technical expertise of the external organization, but they could also use that partnership to train and upskill the wider workforce. This has the added advantage of negating the need to recruit and onboard specialist AI talent at the last minute. Combined with a clear plan of how AI will deliver clear business benefits, it is this action that will drive better, strategic decision-making, whilst leveraging the existing knowledge and value of their own employees.

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