Get Started with AI & Automation

It’s nearly impossible to miss the hype around generative Artificial Intelligence (AI) and automation, but it can seem like technology is advancing too quickly to keep up with. If you find yourself wanting fewer complicated techy words and more practical advice as you get started with AI, you’ve come to the right place.

How do we determine the best place to start with AI? We work through these two exercises (with some feedback loops between them!) to help clients identify an AI first step that they feel confident in.

Complete our AI Best Next Steps Assessment (it’s short, we promise!)

AI is as much a people puzzle as much as it is a technology puzzle. So we’ve created an assessment with tailored recommendations based your team’s unique combination of factors.

On the team front, we know that the most successful AI roll-outs take place within a culture of experimentation and psychological safety. So, we want to set up AI experiments clear success criteria around outcomes, processes, and/or learning objectives. Igniting curiosity about which challenges we can bring to the AI punchlist is one of the results we’re seeking! And, ultimately, we’re in search of strategic adaptability as companies and individuals navigate the age of AI.

So, we share tailored recommendations based on your team’s unique combination of:

  • Culture & Risk Tolerance

  • AI Experience & Comfort Level

  • Readiness to Act

Team Readiness

Of course, our teams can be fully ready to benefit from AI and our technology still hold us back. Data is getting more (not less!) important in the age of AI. While AI can help us mitigate some data quality issues (finding patterns where they weren’t obvious to us, or speeding up profiling efforts, for instance), we still want clean, organized data to feed into our AI projects as much as possible. This will help us draw the right conclusions and build the team’s confidence in continued reliability.

We can also consider processes in technical readiness. For instance, OCR (optical character recognition) and purposeful machine learning can dramatically increase the efficiency of processing invoices. We can go from manually entering each data element to simply verifying that the invoice was processed and coded correctly, with some time spent setting up the vendor’s invoice template and directing/checking the automatic processing three to five times. Now that’s real progress!

With all of that in mind, we assess respondents’ readiness for, and include tailored coaching around:

  • AI Roadmap Stage

  • Technical Foundation

  • Budget & Investment Evaluation

Take the assessment for coaching on your best next steps in AI.

Technical Readiness

We want to address challenges and opportunities already in your sights, with the art of the possible in AI and automation.

It’s enticing to dream up the best first AI initiative for a team or organization. But we can miss out on value by veering too far outside of your current objectives when identifying a starter AI initiative.

So, look at your goals, objectives, and challenges in the next quarter or two: where can AI and automation fit in to drive success? If where you are and where you can be with AI just seem too far apart, we’ve compiled some AI and automation use cases to spark your thinking.

Read through these and jot down the ones that feel the most “you” — then we can discuss how to apply them to your specific circumstances.

Financial Services

Every churn story leaves breadcrumbs: fewer logins, smaller deposits, a frustrated chat. Predictive models read those hints early, score each client’s flight risk, and trigger personalized outreach. Result: the right nudge turns “I’m leaving” into “I’m staying.”

Keep customers from walking

Imagine a loan application that originates in Buenos Aires moments after the same borrower’s phone logs in from Dallas. Real-time fraud engines flag the geographic mismatch in milliseconds, freeze the application, and alert the lending team before a single dollar is approved. Result: fewer charge-offs, protected capital, and underwriters who finally sleep at night.

Spot fraud as it happens

Business clients’ health shows in their transaction flows: supplier payment delays, customer concentration shifts, seasonal pattern breaks. AI spots trouble brewing in commercial portfolios before financial statements reveal it. Result: proactive restructuring saves relationships and recovery rates soar.

Early warning radar

Healthcare

Genetic data, wearable vitals, and lifestyle notes merge into a single data driven lifestyle map. Decision-support models match that map to health recommendations with the best projected response. Result: trial-and-error shrinks and outcomes soar.

Care tailored like a fingerprint

Discharge notes, medication adherence, and social determinants paint a picture of who's coming back. AI flags high-risk patients and triggers interventions: home health visits, pharmacy check-ins, transport assistance. Result: readmission rates drop and patient outcomes improve.

Readmission crystal ball

A diagnosis often arrives wrapped in jargon. Large-language models translate charts into everyday words, surface next steps, and answer questions 24/7. Result: informed patients stay on plan instead of spiraling on search engines.

Plain-English care guides

Non-Profit

Each grantor wants metrics in a different template. Document-generation tools pull live data, craft narrative, and align visuals to every guideline. Result: staff swap late-night formatting for strategic relationship-building.

Grant reports that write themselves

Thank-you emails get opened less often and event RSVPs start declining. Engagement models spot these subtle shifts, identify supporters who need attention, and trigger personalized outreach at just the right moment. Result: donors feel valued and stay committed to the cause.

Donor churn signals before the dip

Wealth events — IPOs, acquisitions, tax years — create giving windows. AI monitors public filings and news to time major gift asks perfectly. Result: larger donations from willing donors approached at the right moment.

Major gift timing guru

Retail & E-commerce

Botnets and reshipping rings mimic good shoppers until the refund hits. Pattern-recognition engines vet each cart in milliseconds, quarantining risky orders before chargebacks land. Result: revenue stays intact, and trust keeps climbing.

Fraudsters stopped at checkout

TikTok makes your random SKU famous at 9 PM. By 9:15, AI has shifted inventory from sleepy stores to hot zones, bumped the product in search results, and queued the reorder. It rides viral waves while competitors watch from shore. Result: capture lightning in a bottle and turn memes into margins.

The trend surfer

Competitors change prices 50 times daily. AI monitors the battlefield, adjusts your prices within profitable bounds, and knows when to match versus when to hold. Result: smart pricing that protects the bottom line.

Price wars you win

Telecom

Premium phones and streaming boxes disappear between “shipped” and “activated.” AI connects the dots: shipping addresses with no service history, identity mismatches, and velocity patterns that scream fraud. It flags suspicious orders before FedEx picks up. Result: $1000 devices stay out of reseller markets, fraud losses plummet, and genuine customers get their upgrades faster.

Device vanishing act detector

A one-size script nudges one customer yet alienates another. AI models choose the right channel, message, and timing most likely to secure payment based on actual payment data. Result: recovery rates climb and goodwill survives the process.

Collections with precision timing

Population shifts, construction permits, and usage patterns reveal where tomorrow’s capacity crunches will hit. AI prioritizes infrastructure investments for maximum ROI and customer satisfaction. Result: capital deployed where growth happens, not where it happened.

Network investment oracle

M&A

Sellers bury problems in footnotes, spreadsheet tabs, and email chains. AI excavates through terabytes of unstructured data — finding related-party transactions in contracts, employee exodus patterns in org charts, and customer defection hints in support tickets. Result: uncover hidden liabilities that kill deals or slash valuations.

Red flag archaeologist

Email patterns, org structures, and communication styles predict which mergers sing and which explode. AI analyzes both companies’ digital DNA—response times, decision chains, language patterns to map integration friction before Day One. Result: retention plans that work, integration costs that don’t spiral, and efficiencies that actually materialize.

Culture clash crystal ball

Every integration has an optimal pace — too fast breaks things, too slow loses momentum. AI monitors employee stress signals, customer satisfaction metrics, and operational KPIs to dynamically adjust integration velocity. It knows when to push and when to pause. Result: capture synergies without culture crashes and hit targets without hitting walls.

Smart integration throttle

Manufacturing

Port backlogs, currency swings, and inclement weather all disrupt demand. Forecast models fuse those signals to schedule production, shipping, and reorder points with new precision. Result: customers receive on-time deliveries even when the world changes.

Supply chains with a sixth sense

Defects hide in patterns humans miss: temperature drift, pressure wobbles, missing quality check. AI spots the tell-tale signs in real-time sensor streams and prevents bad batches before they happen. Result: scrap rates nosedive and customers stop calling angry.

The quality whisperer

Carbon emissions hide in supply chains. AI traces carbon through every component, process, and shipment, suggesting substitutions that cut footprint without cutting quality. Result: sustainability goals met and green premiums captured.

Sustainability calculator

Energy

Equipment doesn’t fail without warning: subtle signals are present. AI listens to vibration, temperature, and pressure data in real time to predict when equipment is more likely to fail. Result: less downtime and longer equipment life due to planned service replacing costly emergency repairs.

No more surprise shutdowns

Sending the closest technician isn’t always the smartest move. AI matches job needs with tech skills, available inventory, and current location to build the optimal dispatch plan. Result: less windshield time, faster fixes, and more jobs done per day.

Optimized technician dispatch & routing

Every kilowatt has a carbon footprint that changes hourly as different power plants turn on and off. AI tracks the real-time carbon intensity of electricity and helps large users shift their consumption to cleaner hours. Result: same operations, lower emissions, and verified data for sustainability reports.

Carbon tracking that actually works

Interested in exploring how to get started with AI?

Set up time with a FlexPoint leader to discuss custom recommendations based on your assessment responses and which use cases resonate most.

(No cost, and no pressure to proceed further. We want to help you get a strong start with AI!)