Embracing the future: The era of "AI First" in business strategy
Written by Jens Eriksvik & Peter Wahlgren
Remember the terms “Cloud first” and “Mobile first” and how these guided decision-making and approaches over the last 15 years - are we now embarking on the era of “AI first”? The technological landscape has undergone a series of transformative shifts, each revolutionizing the way businesses operate and interact with the world. Like with cloud and mobile, the idea of "AI First" is yet paradigm shift, reshaping how leaders should approach decision-making, investments, and project portfolio management.
"AI First" is not merely about incorporating AI technologies into existing processes; it’s about integrating AI into the very foundation of business decision-making. It's about shifting from a tech-first approach, where AI is an afterthought, to an AI-first approach, where AI is the driving force behind innovation and growth. This paradigm shift requires a fundamental transformation in mindset, empowering businesses to harness the power of AI to address complex challenges and seize new opportunities.
“AI first” in business
An “AI first” mindset means placing AI at the forefront of decision-making, prioritizing AI when making investments, and aligning AI to support project portfolio management goals. This departure from traditional tech-first approaches emphasizes the proactive integration of AI into every aspect of the business. It means challenging yourself in everything you do.
An AI first approach to business strategy has implications for individual managers on a daily basis. Here are some specific examples of questions to ask yourself regularly:
Decision-making: How can AI help me in making this decision? This means to always reflect on how AI can improve your decision-making, whenever faced with a decision.
Lead by example by making AI work for yourself: How can I can integrate AI tools into my daily workflows to automate tasks, improve decision-making, and gain insights from data? For example, a manager could use AI-powered scheduling tools to optimize schedules, AI-powered customer relationship management tools to analyze customer data, or AI-powered predictive analytics tools to forecast sales. Or, how do I make the most our of co-pilot?
Embace continuous learning: How can I stay up to date with the latest AI advancements to effectively use AI tools and make informed decisions about AI investments? This means reading industry publications, attending conferences, and taking online courses.
Foster a culture of innovation: How can I foster a culture of innovation by encouraging employees to experiment with AI tools? This means leadership and establishing approaches to providing training on AI, AI ethics and responsible AI development, and holding brainstorming sessions to generate new AI-powered ideas.
"Adopting an 'AI First' mindset isn't just about using the latest technology; it's about reshaping our approach to problem-solving and innovation. By prioritizing AI, we can unlock new opportunities and drive significant progress across various industries."
-Peter Wahlgren, Managing partner at Algorithma
Senior leadership should champion the AI first approach
Senior executives play a pivotal role in shaping the organization's overall AI strategy and ensuring that AI investments align with long-term business objectives. They must champion an "AI first" approach, fostering an organizational culture that embraces AI as a transformative force.
Establishing AI vision and strategy: Clearly articulate the organization's AI vision and strategy, outlining the desired outcomes and the role of AI in achieving them. This vision should be aligned with the overall business strategy and should guide all strategic initiatives.
Prioritizing AI investments: Allocate resources to maximize return on investment considering AI capabilities. This requires careful evaluation of potential projects, considering factors such as feasibility, impact, and alignment with business goals.
Overseeing AI project portfolio: Stay close to the project portfolio, challenging your teams to rethink the approach and leverage “AI first” throughout.
“AI first” for strategic decision-making
When making strategy decisions, of course, it is not only about challenging one self to consider AI, it is about a structured approach. Consider the following aspects, some which are long-standing perspectives of decision-making:
Understanding the problem: Clearly define the business problem or challenge that AI is intended to address. This involves identifying the root cause of the problem and understanding the desired outcomes.
Assessing AI potential: Evaluate the potential of AI to solve the identified problem. Consider the capabilities of AI technologies and their applicability to the specific context.
Weighing AI benefits and risks: Assess the potential benefits and risks of implementing AI. Consider factors such as cost, efficiency, accuracy, and potential ethical implications.
Identifying data requirements: Determine the data needed to train and operate AI models. Assess the availability and quality of relevant data.
Evaluating alternative approaches: Explore alternative approaches to solving the problem, including traditional methods and non-AI solutions.
Building a cross-functional team: Form a cross-functional team with expertise in AI, business, and domain knowledge to make informed decisions.
Continuous monitoring and iteration: Continuously monitor the effectiveness of AI solutions and make adjustments as needed.
”AI first” is, like the predecessors “Mobile first” and “Cloud first”, a shift in mindset more than anything. While it may seem abstract at first, it is possible to approach it with a playful perspective and a spirit of experimentation, you can unlock its full potential and transform businesses for the better. Senior leaders need to champion the change, to be early adopters and walk the talk to enable transformative change.
Through an “AI first” approach, you increase the likelihood that AI is effectively integrated into the organization's strategic decision-making process, leading to impactful and sustainable AI initiatives.