Everyone is saying that “you need AI” but nobody is telling you how to get started
How we enable companies to hit the ground running
When it comes to embracing AI, business leaders appear to think it’s a case of the “Emperor’s New Clothes.” Lots of “oohs and aahs” but no proof of its real-world benefits which could prompt them to take it seriously.
AI has the potential to disrupt any business by highlighting previously invisible patterns, insights or networks within a company, yet it requires a systematic shift in thinking about the business. From product development at Coca-Cola and safety management at Volvo to fraud detection at Amex and checkout-free shopping experience at Amazon, we have all heard of innovating companies that are proving AI can drive a systemic change.
Part of the problem is that it’s hard to understand how to apply AI to your own organizations in a way that achieves meaningful impact. At ML2GROW we got you covered: we have deployed more than 75 use cases in more than 12 sectors leading to solid foundation of inspiration to get you going. Combined with our solid approach to start your AI journey we can advise and guide you from beginning till the end.
Your AI journey will involve four phases:
PHASE 1: SET UP FOR SUCCESS
- Incorporate AI in the company’s vision & strategy
- Explain the ‘why’ of AI and anticipate the barriers to change
- Already plan for the last mile (i.e. integration) as the return on investment starts there
Phase 2A. DELIVERY
- Establish multidisciplinary teams to iterate short cycles to experiment (especially in the initial stages)
- Follow strictly a delivery methodology incorporating these stages; experiment, integrate, improve and repeat – every step has its own challenges
Phase 2B. BUILDING AI MATURITY
- Educate everyone about the fundamentals of AI
- Shift towards a culture of experimentation & cross-collaboration
- Establish a ‘Center of Excellence in AI’
Phase 3. REINFORCE
- Track & facilitate adoption
- Expanding AI initiatives through iteration
Assess and expand your in-house AI capabilities in the organisation
How we help you create value with AI
One of the biggest misconceptions about AI is to view it as a “plug-and-play technology” that will simply generate results once deployed. AI simply cannot be compared with traditional software in which procedures and processes have been hard-coded by humans to be as efficient as possible. AI software will use your own data to deliver the predictions and insights that are relevant to you. Therefore it’s much harder to buy a value-generating AI program, but with your data, you should definitely consider creating one.
The disruptive nature of the technology can cause established organizations that have rigid structures, strict processes and procedures to struggle to extract all value out of AI systems. Establishing a sustainable AI adoption, therefore, requires a significant transformation towards more agility. Therefore, simply investing in AI software tools, data infrastructure and development skills will not be enough once you plan to incorporate AI into the core activities of your organization. It will need to be aligned with the company culture, structure and way of working to achieve its full benefits.
According to McKinsey, “most businesses that aren’t born-digital, traditional mindsets and ways of working run counter to those needed for AI.” To maximize the potential of artificial intelligence adoption, many businesses must work towards changing these traditional views to fully embrace the digital era.
For a broad AI adoption three main shifts will be crucial:
- Shifting from expertise & experience-based decision making by top management to data-based decision making by first-line employee’s (shift in responsibilities)
- Shifting from siloed work to interdisciplinary collaboration. All data is being generated across the organization but trusted and being used by others. It’s important that everyone understand his/her role in the bigger play.
- Given AI models are agile and swift, rigidness and risk-averse ways of working will counter the benefits of the AI model. A shift towards the agile, iterative and experimental ways of working will be needed.
Of course, as always, it’s crucial to start small but thinks big. Every organization is completely different therefore a ‘silver bullet solution’ doesn’t exist. An experimental small approach will allow finding the optimal route in your transformation journey. ML2GROW has already established a blueprint of what will be required in your AI transformation. Let’s discuss what’s still needed, have a complimentary talk with our experts.