If you were to say that the pandemic changed the whole course of technology in business, you would only be partially correct. In truth, what the pandemic did was push us further and faster along a path we were already heading down. Digital transformation and artificial intelligence (AI) adoption have been on the annual strategic agenda for many businesses for the past several years, mainly as an exploratory item. At the start of 2020, the average global share of products and/or services that were partially or fully digitised was at 35%. By the midway point to the year, that figure had jumped to 55%, indicating that the onset of the pandemic led to approximately seven years’ worth of progress in around six months[1].
Now that we are well on the path to some version of recovery, no one is going to drop their tools, say “Well, that was fun while it lasted,” and go back to the way things were before we realised we could do it all differently. Nor should we go back. The pandemic not only changed the market conditions that leaders must navigate in order to keep driving their business forward, but also changed the way they need to lead within new target operating models.
Much has been said about AI’s potential benefits for different business functions, but can this technology help leaders bridge some of their key people management challenges? We explore the question in 5 key areas:
Just as businesses have begun using more technology in their day-to-day practices, so have their customers. Every website visit, virtual appointment, online communication, and social media interaction creates a data story that can tell business leaders more about their consumers needs, habits, wants, lifestyles, and feelings. But the problem usually is that most businesses have no idea what to do with any of this data or no way to make sense of it.
That’s where AI comes in. These tools can continuously collect, process, and analyse large volumes of data quicker and in more detail than any human could possibly replicate. This data is translated into more digestible formats for easier analysis, detailed forecasts, and insightful recommendations that bring focus to leaders and their teams more quickly. This analysis might reveal trends to expect, issues that have been overlooked, or areas for improvement.
Collecting and making sense of this data will fall on technology, but it is up to leaders to decide what they want to do with it. AI gives leaders the clearest picture possible of what they are up against and where the opportunities are. Because these tools work continuously and provide insights in real time, leaders can act fast to course correct and keep their finger on the pulse of an ever-changing consumer market. This capability will become increasingly valuable as global competition rises and the customer journey continues to evolve.
Issues of diversity, inclusion, and equality have been thrust squarely into the spotlight as several societal conflicts have arisen this past year. As a result, many decision-makers are taking more purpose-led approaches to leadership (we have a blog on that here) and prioritising these issues in their company’s strategy. For these efforts to be genuine, they need to be reflected in the makeup of the organisation.
AI helps to build more diverse teams through hiring by eliminating some of the inherent biases that human decision-makers may unknowingly bring with them into the process. By automating everything from scanning CVs to conducting early rounds of interviews, AI is able to keep the process as impartial as possible. Of course, this does not always work as intended. AI follows the algorithms that it is trained on, so if it is fed biased information its outputs will reflect that. For example, perhaps the algorithm is trained to hire candidates that sound like a good fit for the organisation and was trained to determine this ‘fit’ based on the organisation’s current team. If the existing staff is predominantly male, all went to a certain set of schools, or are a certain racial background, then the algorithm will most likely select candidates that also possess these attributes. Some have tried to counteract this by programming the algorithm to seek out clearly diverse candidates, but this practice of ‘token’ hiring has raised questions of whether this is a truly fair practice.
It is important for leaders to remain conscious of the suggestibility of algorithms if using AI tools with this purpose, but when programmed correctly these tools can facilitate more equal hiring and help to minimise some of the bias that presents itself in the process.
Beyond promoting more diversity, AI can make it easier to build the right team and support their growth long term. As mentioned, automation can be used to streamline some of the process, such as scanning CVs for keywords in order to narrow down your candidate pool. While this initial screening will likely be handled below the management level, the increased accuracy of this process helps to ensure that the candidates presented to decision-makers are the best talent available for the role.
Additionally, these tools can help ensure you match the right talent to the right roles, every time. This is typically accomplished through the use of augmented and autonomous AI to personalise the experience and guide the candidate to the role that best matches their capabilities. This makes it easier for the leader to ensure that they have the right skills on their team and the support they will need for long-term success.
Integrating new talent to your team is another area where AI thrives. Technology can help to improve the onboarding process by getting new hires up to speed efficiently and via a more tailored experience. For example, there are tools available that can match a new employee’s preferences with recommendations about which benefits package best suits their needs. Starting employees off on the right foot helps to improve long-term retention, meaning leaders can focus their attention on achieving objectives rather than worrying about their team.
While many organisations may be actively recruiting and some leaders are having to build and onboard new teams, others have focused their attention on their existing staff. The adoption of new technology impacts all parts of the organisation, not just those at the top. If new tools are being introduced, then training and upskilling activities may need to be undertaken in order to ensure the team has the right capabilities to use them effectively. But your people don’t know what they don’t know, and as a leader, you should never assume that all members of your team are on the same level of capability and comfort with using technology.
AI learning tools can not only assess your team’s current level of knowledge but also meet them where they are. The use of personalised learning tools in L&D functions is on the rise due to their ability to tailor training to suit individual skill levels and learning styles. For example, these tools might offer staff a series of questions or activities. On the back end, AI and machine learning algorithms are analysing the responses to pinpoint the individual’s level of understanding of the topic at hand. Based on this assessment, the platform may offer the information in a new format that is more suited to the individual’s learning style and repeat the lesson until the information is absorbed, or may deem it suitable to move on to the next lesson.
For leaders, this helps to ensure that staff are getting the necessary training in the most effective way possible. Training can be a costly expense for businesses and approaching this in a one-size-fits-all way cannot ensure effectiveness. Tailoring training to your team helps to engage them in their learning and provide the best chance at absorbing these new skills.
In an ideal world, every team member would be perfectly satisfied in their role and your best team members would stick around forever. But that is not our world, and therefore leaders need to pay attention to their team’s needs, levels of engagement and team atmosphere.
Sentiment analysis tools are able to assess employee communications to identify potential dissatisfaction, while intelligent employee surveying can be used to gather insights directly from staff about their feelings. If an employee is showing signs of displeasure, AI algorithms can be trained to identify patterns that suggest when they may be ready to turn over. The system would then send an alert to the HR team, allowing them to intervene before it’s too late. In some cases, this desire to leave is tied to compensation. AI tools can analyse market factors, the employee’s performance, and their job achievement to help suggest compensation.
Beyond holding onto staff that is on the verge of turning over, AI can help your team progress within the organisation. Some talent intelligence platforms are able to provide personalised career guidance to employees based on their innate capabilities, potential, and future positions of interest to encourage long-term planning. Some companies use this intelligence to match employees with mentors in the organisation who can provide relevant advice related to that individual’s identified pathway. Additionally, these tools can help to identify higher performers who may be ready for the next level or may be well suited to a leadership opportunity.
The mark of a successful leader is a successful team. By partnering with AI, leaders can conduct more regular temperature checks with their people and intervene before issues can have negative consequences.
It’s clear that AI can take on some of the heavy lifting of leaders’ people management responsibilities, but it should be noted that this technology should be treated as a tool rather than a replacement. Leaders should not become complacent and expect that AI will solve all their problems. There still needs to be a ‘human touch’ involved, especially in matters of people management. When considering AI, leaders should simultaneously work to adapt their own styles and skillsets in order to incorporate these tools into their style of leadership, but should not lose sight of all the attributes that make them a strong leader in the first place.
[1] https://www.mckinsey.com/business-functions/strategy-and-corporate-finance/our-insights/how-covid-19-has-pushed-companies-over-the-technology-tipping-point-and-transformed-business-forever
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