A.I. and Achieving Real Business Differentiation – Part 5 – Knowing the Pitfalls

In our ongoing series "A.I. and Achieving Real Business Differentiation," we covered from the risk of sameness due to AI, discussed the importance of leadership change and highlighted the criticality of engaging the right partner. Harnessing the power of AI requires navigating potential pitfalls. Past experiences reveal a recurring pattern in transformations across a variety of businesses, where similar challenges repeat time and time.

For every revolution,  the evangelists, champions, innovators, early adopters, and others often claim uniqueness, dismissing past lessons as irrelevant. As the Spanish-American philosopher George Santayana famously remarked, "Those who cannot remember the past are condemned to repeat it," and echoing this sentiment, American writer Cassandra Clare asserted, "Knowing is better than not knowing." 

This article, part of our ongoing series, explores common challenges businesses face when integrating AI, particularly SMEs with limited resources. While AI presents an exciting opportunity, neglecting these pitfalls can significantly derail your efforts.

Addressing Pitfalls for a Successful AI Journey:

1. Return on Investment (ROI):

• Pitfalls: Setting unrealistic or vague ROI expectations, especially when benefits are intangible or take time to materialise.
• Solution: 
1. Partner with a consultant that has experience establishing business case for AI journey.
2. Develop an MVP/prototype to establish initial insights and refine investment plans.
• Additional Tip: There is nothing wrong with being in this situation at the start of the journey. However, regularly reviewing and updating ROI calculations as the project progresses to strengthen the business case and avoid surprises at the end is good practice.

2. Loose/Ambiguous Objectives:

• Pitfalls: A common pitfall is not to invest the time and the resources to clearly lay the business needs and objectives to achieve. Additionally, the ambiguity and lack of clarity in loose objectives can lead to some challenges in holding individuals or teams accountable for achieving them.
• Solution: Invest time and resources in outlining tangible and measurable goals.

• Additional Tip:
  • Encourage regular reassessment and refinement of objectives throughout the project and verify the business case validity.
  • Remember, a change initiative that is primarily driven by technology is prone to failure (see A.I. and Achieving Real Business Differentiation – Part 2). So, do not ignore the people and the operational aspects that AI will impact when introduced in the definition of the objectives.

3. Budget and Cost:

• Pitfalls: 
1. Underestimating costs driving the wrong budget decision/ allocation, 
2. Losing track of expenditures during the implementation.
3. Challenge for SMEs to investment  in AI technologies, infrastructure, and expertise due to tighter operating margin.
• Solution: 
1. Allocate realistic budgets and do not over optimise the cost. Our experience shows that the cost of doing things is always more than what people initially thinks. Therefore, plan some contingency to mitigate this.
2. Implement project management. If the business does not have the skill in house, consider hiring a professional.
3. Collaborate with a partner under the term of a fix price contract, mitigating the risk of going over budget
• Additional Tip: 

• Create a business worst case scenario integrating the assumption that the whole contingency is spent. Businesses should always have in mind the value of the minimum ROI that could be reached.

• AI is the next evolution that businesses cannot afford to ignore if they wish to continue to have a viable future. For this reason, a business should never hesitate to bring the necessary expertise, if in doubt.
• There is a line of thought that project management is not necessary. Unfortunately, experience shows the contrary. Remember the elephant in the room mentioned in our Part 3: every investment is costly until a return of investment is delivered!

4. People and Change Management:

• Pitfalls: 
• Resistance to change driven by a lack of engagement with staff affected.
• No training covering culture and process changes associated to AI introduction.
• Solution: 
• Proactively engage people impacted. As explained in our Part 3 article, the business leadership team is key in bringing the staff on this AI journey.
• Develop a training plan that does not cover only how to implement and use the new AI tools but also transform how people work within an AI-rich environment.
• Emphasize AI's positive impact on work culture.

• Additional Tip:
  • Consider leadership training as well as AI impacts on the work culture.
  • Consider upskilling junior staff into current process allowing to free the in-house business process experts for the AI journey.

5. Technology Obsolescence and Vendor Dependency:

• Pitfalls: Choosing solutions with limited future-proofing and vendor lock-in.
• Solution: Leverage proof-of-concept approaches to confirm possibility to export the business IP created into a different solution or an open format.
• Additional Tip:  Partner with vendors committed to open data formats in their solution.

6. Integration:

• Pitfalls: Inefficient integration with existing systems and unnecessary complexity of processes preventing the realisation of the ROI.
• Solution: Utilize a system IT architect to maintain the solution on the right path and involve the in-house business process experts in planning and implementation to flush out the unnecessary complexity.
• Additional Tip: Prioritize upskilling junior staff intime prior the in-house experts are needed to support the technical integration activities.

7. Lack of Expertise and Understanding of AI:

• Pitfalls: Limited understanding of AI capabilities and its limitations, as well as struggling to attract or afford specialists due to the high demand and salary expectations in the AI field.
• Solution: Partner with consultants who can provide comprehensive support and cover all relevant aspects of implementation beyond the technology aspect to avoid having an unbalanced approach.
• Additional Tip: Seek resources and educational opportunities to enhance your own and your team's understanding of AI.

Limited budget, lack of expertise and understanding AI capabilities and limitations are typical SME challenges, while loose objectives, people, training, integration, technology obsolescence and vendor dependencies are common to all enterprises. But as an SME you should be aware of them when considering introducing AI.

Remember AI is a great opportunity, but you will have only one chance to integrate it into your business successfully.  If you want to discuss such a journey, please contact us at +44 7473 298 853 or reach out to us via email at francois.contreiras@tinderboxbd.com or send me a message on LinkedIn for a free, no obligation chat to help you forge the future well beyond your competition.

Take Away:

In today's AI-driven landscape, SMEs that effectively leverage AI can outperform and even replace those that do not. Successfully navigating AI's challenges significantly boosts the likelihood of leveraging its transformative potential. Therefore, the key for SMEs is proactive, informed engagement with AI, ensuring not just survival but thriving success in a competitive market.

Note for readers:

• ChatGPT has been used as a proofreading tool to enhance grammar and improve reading fluidity.
• SearchEngineReports.net was employed to identify unintentional plagiarism.