As AI technologies continue to evolve, businesses are experiencing transformative changes across various dimensions, including efficiency, customer experience (CX), decision-making, and innovation. Amidst this profound shift, many leaders are emerging as pivotal figures, wielding influence not only in steering organisations through the complexities of AI adoption but also in harnessing its potential for the greater good. These leaders are the champions of AI, guiding their teams towards innovation, ethical practices, and sustainable growth in an increasingly automated world.
In a 2023 European study of over 1,600 senior leaders and C-suite executives from organisations with 500+ employees, 82% of respondents reported they have already deployed generative AI or intend to employ it in the next year. The pressure for leaders to choose the best tech, allay workforce fears, upskill people, navigate security threats and the regulatory landscape, ensure the business stays ahead of its competitors, and role model desired behaviour … well, that’s a big skillset to master.
Here, we’ve put together a list of the best things you can get to work on right away to help your organisation, no matter where you are on your AI journey.
1. Model the right culture
You don’t need to be an expert in AI, but you do need to actively role model behaviours that enable your organisation to be inquisitive, open minded, and responsive. How can we do this?
Embracing a non-hierarchical structure: In traditional, hierarchical businesses, idea generation usually stays within the C-suite. In today’s fast-paced world, Gen-Z digital natives are playing an increasingly important role and leaders must be open to new opportunities and product ideas from their teams. Be open to learning from one another.
Cultivate a culture of experimentation: A culture of experimentation means embracing failure rather than seeing it as a setback. Leaders must empower their teams to explore AI’s possibilities and drive meaningful change within their organisations. Fostering an environment that encourages curiosity and risk-taking.
Diversity of thinking: By embracing diversity in thought and experience, the creative process is enriched and will uncover insights that propel AI initiatives forward while mitigating potential blind spots. Successful AI implementation often requires input from various departments, including IT, data science, operations, and business units. Leaders should build a cross-functional team to ensure that all perspectives are considered and the implementation aligns with overall business goals. Bring people of all levels and experience together to create an opportunity for everyone to learn. Have AI champions across the business to scale initiatives.
2. Invest in your people
By investing in your people and giving them the right skills, you are equipping your business with the ultimate differentiator. Turning vision into reality for AI is challenging, and failing to understand how the workforce needs to adjust in order to succeed could cause huge problems.
Create a talent strategy: A talent strategy identifies how work will change. Document the impact to roles and assess what skills are needed for every Gen AI use case. Invest in continuous learning and upskilling to equip teams with a skillset that combines technical and data expertise with soft skills and commercial acumen. New skills such as AI can be layered onto existing expertise, leading to faster results without the requirement to recruit and train new joiners.
Prioritise internal programmes: By prioritising internal programmes/training and creating pathways for skill development, leaders will empower individuals to harness the full potential of AI and drive innovation from within.
Remember that investing in learning is not a one-off thing; we are at the beginning of our understanding of AI and therefore learning will be an ongoing investment.
3. Champion ethical practices & transparency
Leaders bear the responsibility of ensuring that AI technologies are deployed with integrity, fairness, and transparency. They must navigate complex moral dilemmas, such as bias in algorithms, data privacy concerns, and the implications of automation on employment.
By championing ethical AI practices, leaders uphold trust among stakeholders and pave the way for responsible innovation.
This means taking intentional actions to design, deploy, and use AI to create value and build trust by protecting the organisation and its people from potential risks. Maintain high standards of trust, transparency, and sustainability in every generative AI-driven initiative.
Establishing principles: These principles will form the basis for all decision making and it is the job of leaders to ensure these principles are adhered to. Recently, one of our clients introduced AI tools and created a policy that “No AI could be copied and pasted directly. Users have to use their own judgement before using the output”. This provided a necessary check in the process and it was a signal to employees that the organisation trusted their judgement when using it.
Conduct a risk assessment: Understand the risks of any existing AI use cases, applications, and systems through qualitative and quantitative assessments (e.g., fairness, explainability, transparency, accuracy, safety, human impact, etc.). Tools such as the Assessment List for Trustworthy AI (ALTAI) can be used to try to anticipate and mitigate AI risks before they occur.
Key Performance Indicators (KPIs): Establish KPIs and metrics to measure the success of AI implementation efforts. This will move the conversation from commitment to ethical practices to action on the ground. It also creates a more trusting and transparent culture that will ease concerns. Regularly monitor progress against these metrics, identify areas for improvement, and make adjustments to the AI strategy as needed to drive better outcomes.
Effective leadership will be essential when it comes to navigating the opportunities and challenges presented by AI. We need to ensure that AI technologies are developed and deployed in a responsible and inclusive manner. By modelling the right culture, committing to people, and championing ethical practices and transparency, the journey will be a smoother one.
Interested in implementing AI at your organisation, or exploring how to manage a tech transformation? Get in touch with one of our experts!
