Can Your Business Survive the AI Revolution Without a Technical Background?

Is Your Team Ready for AI, or Are You Just Following the Hype?

Don’t get left behind in the AI revolution. Read our summary of Your AI Survival Guide by Sol Rashidi to learn practical steps for deploying AI, managing teams, and avoiding costly mistakes—no coding required.

Are you ready to move from AI buzzwords to business results? Stop guessing and start leading. Get your copy of Your AI Survival Guide and discover the exact frameworks used by industry veterans to launch successful, ethical, and profitable AI projects.

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In the age of AI, non-technical business leaders can’t afford to stay on the sidelines. They must learn to work knowledgeably with their IT teams to establish and implement a successful AI strategy. Sol Rashidi, an AI deployment veteran who helped launch IBM’s Watson — one of the earliest AI applications — is here to help. Rashidi outlines everything you need to do on both technical and managerial levels to deploy AI, from uncovering your “why,” to building your team, to making your AI responsible. As AI transforms everything from agriculture to HR, the time to be proactive is now.

Take-Aways

• Implementing AI within your company is not an all-or-nothing proposition.
• Assess which AI strategy fits you and your team.
• Select relevant use cases.
• Plan how to launch your AI project well.
• Choose the right tools and partner with the right experts before going live.
• Ensure your team is gritty, ambitious, and resilient.
• Incorporate human oversight into AI decision-making.
• AI will transform everything from agriculture to education to litigation to marketing.
• AI will drive trends and raise new challenges for businesses.

Summary

Implementing AI within your company is not an all-or-nothing proposition.

Preparing to launch an AI project requires you to find a balance between your organization’s established protocols and the need to adapt to changing times.

“Bending the rules sometimes means having to risk popularity for progress without breaking your spirit and compromising your well-being.”

Deploy AI successfully by doing the following:

1. “Ask ‘why?’” — Reflect on why you want to deploy AI. Is it to streamline business operations before selling to a private equity firm or to stay competitive in a challenging environment? Discuss your why with your team to find alignment and avoid confusion.
2. Develop your AI strategy — Depending on your business’s current capabilities, you may use an “efficiency strategy” — doing what’s right with minimal waste; an “effectiveness strategy” — reaching your desired outcome perfectly; a “productivity strategy” — maximizing output while tolerating inaccuracies; an “expert strategy” — solving specific problems with a team of domain experts; or a “growth strategy” — boosting external growth such as social media traffic or market share.
3. “Think big, start small, scale quickly” — Imagine what’s possible, scan for opportunities, and start small by finding a suitable AI use case. When it’s time to scale, move quickly.
4. Choose your technology partner — Partner with a qualified AI consultant, development firm, or adviser that fits your budget and goals.
5. “Pace yourself” — Set a realistic pace for your AI project.

Assess which AI strategy fits you and your team.

An AI “readiness assessment” helps you determine which AI strategy — “efficiency,” “effectiveness,” “productivity,” “expert,” or “growth” — is best for you. To conduct this assessment, answer the following questions for each category, scoring yourself on a scale from one to five:

• “Market strategy” — How well do you understand the growth opportunities in your business and market? How comprehensively have you identified your primary sources of competition and disruption?
• “Business understanding” — How actively are you addressing current company problems? How are accountability, workflows, and other business processes aligned across teams and functions?
• “Workforce acumen” — How strong is your organization’s specialization, domain expertise, and business acumen? Is your team ready to innovate and value opportunities over risks?
• “Company culture” — Does your company value innovation and adaptability? Does leadership drive teams to be more efficient, effective, and productive?
• Role of technology — How much of a strategic priority is new technology? How reliable and knowledgeable is your technology team?
• Data — How accessible, available, and clean is the data you need?

Add up your score to choose an appropriate AI strategy. Companies with low scores — from two to four — will do well with efficiency or productivity strategies. Those with mid-range scores of four to seven can expand to effectiveness strategies, and those with scores of eight or higher can consider all five strategies.

Select relevant use cases.

Select relevant use cases that align with the AI strategy you chose. Gather a team of growth-minded individuals, reiterate your why for the AI project, recap your chosen AI strategy, and brainstorm all potential use cases.

Measure the criticality and complexity of each use case. For criticality — how critical the use case is to your company’s success — give your organization a score from one to five for each of these questions:

• Will it affect sales and growth?
• Will it affect operations?
• Will it affect your company’s culture or the public’s perception?

For complexity — how challenging the use case will be to deploy — do the same for these:

• Will AI affect resources for other projects?
• How much change management will be required?
• Do you know who owns the use case?

Plan how to launch your AI project well.

Outline your vision to ensure goal alignment. Share why you’re undertaking this AI project, explain its business value, define a successful end-state, and name key performance indicators (KPIs) and the project’s overall scope. Identify and discuss any potentially harmful effects, including ethical concerns, bad PR, data risks, AI changing job functions, and any issues with partnerships.

“Most projects don’t fail because of bad intentions; most projects fail because of bad planning.”

Focus on project management by defining roles and deliverables and tracking progress. Prioritize change management, “talent training,” “ownership and accountability,” “stakeholder identification,” communications, and staffing.

Align goals, methods, and expectations. Define your desired outcome — for example, building a minimum viable product (MVP) for an efficiency strategy or a proof of concept (POC) for a growth strategy — and establish performance benchmarks. Clarify who’s accountable for code maintenance and budget oversight, and prepare a response plan for dealing with unexpected issues.

Outline your plan for post-launch support, including ongoing maintenance, enterprise integration, and security measures. Establish a risk mitigation process for handling unintended consequences and define who is responsible for what.

Choose the right tools and partner with the right experts before going live.

Choose the right AI tool according to your needs and expertise. Options range from low-cost, low-customization, off-the-shelf solutions to high-cost, highly customized tools requiring technical expertise. For most businesses, off-the-shelf AI tools are the best choice for tasks such as summarizing calls, creating content, and managing marketing.

“While manuals serve as a guide, the real learnings come from doing.”

Given the high failure rate among AI start-ups, research options, assess risks and rewards, and consider pricing, security, and company stability. Collaborate with experts to create standard operating procedures (SOPs).

Ensure your team is gritty, ambitious, and resilient.

In addition to those three virtues, familiarize yourself with these AI archetypes to manage team dynamics and productivity:

• “Naysayers” — Exclude these negative minds from vision meetings; include them in design discussions.
• “Evangelists” — Include these positive leaders in most meetings — but not status updates.
• “Doers” — These task-oriented members focus on execution. Exclude them from high-level talks.
• “Discerners” — Inquisitive types work well in strategic “why” discussions.
• The “Blind” — Exclude disengaged, minimal contributors.
• “Curmudgeons” — Avoid irritable types who dampen morale.
• “Saints” — Include empathetic people in status updates.
• “Optimists” — These positive people contribute little of substance.
• “Data Scientists” — Embrace these individuals for technical design and problem-solving.
• “Know-It-Alls” — Include these dominant personalities in solutions-related conversations; exclude them from vision discussions.

“High-performing teams aren’t born but built.”

To integrate AI successfully, focus on change management. Create a manifesto outlining what you’re doing and why, align your company leadership with its points via office meetings and anonymous Q&As, and plan transitions for individuals and processes while maintaining core operations. Communicate changes regularly. Celebrate small wins, emphasize iteration over perfection, and monitor progress through monthly retrospectives to review progress, issues, and risks. Explain the reasons behind any changes.

Incorporate human oversight into AI decision-making.

AI projects require a “human in the loop” to review AI decisions before the company delivers them to clients or employees. Human oversight provides a framework for developing ethical, transparent, and trustworthy AI systems. Follow these principles to create a simple guide for responsible AI:

“The dangers of AI largely arise from unintended consequences and good intentions going awry.”

1. Transparency — Communicate how you will use AI and collect data.
2. Accountability — Establish responsibility for AI-related issues, such as determining fault in self-driving car accidents.
3. Fairness — Ensure AI systems are free from bias and offer equal opportunities to all users.
4. Privacy — Protect sensitive data and respect user consent.
5. Inclusiveness — Make AI accessible to all.
6. Diversity and nondiscrimination — Use diverse datasets to prevent bias and discriminatory practices in AI.

AI will transform everything from agriculture to education to litigation to marketing.

McKinsey estimates AI will generate $9.5 to $15.4 trillion annually. In agriculture, AI enables precision farming and early pest detection. In manufacturing, it allows for predictive maintenance and quality control. AI personalizes recommendations in retail and generates tailor-made learning materials in education.

“Expand your awareness, foster critical thinking, and embrace your options with an open mind, and you will find yourself not just following but leading in the age of AI.”

Legal professionals can use AI to review contracts and analyze large databases for relevant material for litigation. HR benefits from AI-powered résumé scanning and chatbots for employee queries. Virtual assistants trained on company data help with customer service. Sales teams can leverage AI for automated follow-up emails and personalized pitches.

AI will drive trends and raise new challenges for businesses.

As computational power, data collection, and machine learning progress, AI will drive trends over the next five years. These include automating complex tasks, scaling personalized marketing, and disrupting management consulting by making market research more accessible. AI health data analysis will improve preventative healthcare measures, and small businesses will automate tasks such as accounting, payroll, social media campaigns, and more. This evolution will demand improved AI literacy, governance, and the rise of AI Ethics Officers to ensure compliance.

“Ignoring AI is not an option for businesses that want to remain competitive.”

With AI opportunities, however, come risks such as cyber threats, privacy and bias concerns, and a growing skills gap. To seize the opportunities while mitigating the risks, learn how AI applies to your industry, assess your current capabilities, and identify high-potential use cases. Build a capable team, create a change management plan, keep a human in the loop to catch errors, address ethical issues, and stay updated through forums and partnerships.

About the Author

Sol Rashidi is a business executive, leader, and keynote speaker in the AI, data, and technology space. He has overseen more than three dozen large-scale AI deployments.