We hear about companies across every industry leveraging AI to further business goals, whether it’s cost savings or operational efficiency.
But how are the best companies soaring with AI? Is it all about recruiting the right talent or adopting new tech? McKinsey’s latest quarterly article Rewired to Compete boils down success to six overarching courses of action.
The common denominator? They all stem from the C-suite.
Here are the six moves McKinsey covers in their report:
- Create a roadmap to align the C-suite with common goals
The CEO, CIO, CFO, and every other C-suite member might have different umbrellas of priorities and operational deliverables. Still, AI transformation can’t be successful until each department of a corporation is aligned under a common goal or, in this case, a roadmap.
The C-suite needs to agree on various common goals (and timelines) for digital transformation and focus on a few distinct business domains. Once everyone at the top is aligned, a top-down change can occur.
- Ensure each C-suite department has the right talent
McKinsey’s research outlines the importance of having the right talent pool to conduct all the diverse facets of an AI transformation, from product owners to software developers.
On top of that, the C-suite must assess where upskilling is necessary to ensure 70-80% of talent remains in-house. Outsourcing isn’t a full-scale solution to take an entire company through a digital transformation.
- Change your operating model into one that’s scalable
Transformation and scale go hand in hand, which is why C-suite members must find more efficient processes to speed up transition.
McKinsey identifies three models: digital factory, product, and platform — but the enterprise-agile model is most effective, extending the product and platform model to all areas of the business. For example, this model leverages cross-functional teams to boost performance.
- Make the right software development tools accessible
Prioritize building a self-service portal where every team member can access the tech capabilities they need, rather than placing the obstacle of a tedious IT service desk.
C-suite professionals should also prioritize investment into tech that allows for automation, from quality checks and testing to packaging and deployment.
- Embed and leverage data
If you have a data organization problem, you better fix it before adopting new AI. C-suite professionals can prioritize access to real-time data so their tech professionals can make the most impact with AI.
- Make it an everyday thing.
Final move? Adoption, aka infusing the transformation seamlessly into your users and customers’ everyday experience.
McKinsey says this is the stage that takes the most juice, citing 72% of organizations experiencing “stalling” at deployment and adoption. This process starts with “assetizing” AI solutions to determine repeat use cases for AI, and tracking performance and KPIs over time.
Read the full McKinsey article here.
